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when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', u...\n\nTags: latest:1.0.6\n\nVersion history:\n\nv1.0.6 | 2026-07-16T18:22:27.731Z | user\n\nDescription tail link + agents machine-readable metadata line (deciqai.com/s/zero-sum-game.json)\n\nv1.0.5 | 2026-07-09T11:22:58.435Z | user\n\nRefresh: 2024-2026 AI-era worked examples added (strategy/leadership + systems/game-theory batch)\n\nv1.0.4 | 2026-07-08T11:25:16.810Z | user\n\nFooter now uses /c/ short link (fixes UTM truncation when SKILL.md is read in a terminal)\n\nv1.0.3 | 2026-07-08T03:53:22.373Z | user\n\nSecond primary-sourced worked example\n\nv1.0.2 | 2026-07-08T01:09:26.023Z | user\n\nRefreshed content + GitHub star link in footer\n\nv1.0.1 | 2026-07-07T22:35:13.408Z | user\n\nAdd catalog categories and topics\n\nv1.0.0 | 2026-07-03T16:17:50.041Z | user\n\nInitial publish\n\nArchive index:\n\nArchive v1.0.6: 7 files, 16147 bytes\n\nFiles: examples/ai-competition-fixed-vs-growing-pie-2024-2026.md (7842b), examples/smoot-hawley-tariff-1930.md (4482b), examples/von-neumann-rand-1944-1950.md (3207b), references/sources.md (3275b), skill-card.md (3096b), SKILL.md (10394b), _meta.json (132b)\n\nFile v1.0.6:SKILL.md\n\n---\nname: zero-sum-game\ndescription: \"Activate when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', uses phrases like 'winner-take-all', 'race to the bottom', or 'your gain is my loss', or needs to check whether a negotiation/market/policy situation is truly zero-sum before designing strategy.\n Do NOT activate when: the situation is already confirmed zero-sum (chess, derivatives, fixed-license auctions) and diagnosis is complete — go straight to minimax; or the question is already framed at the equilibrium level — use nash-equilibrium directly. More: deciqai.com/c/zero-sum-game\"\n---\n\n# Zero-Sum Game\n\n## Overview\n\nZero-sum means total value is fixed — one player's gain is another's exact loss. Most real-world competition is NOT zero-sum: the pie can grow, shrink, or be split in many ways. Misdiagnosis sends strategy in the wrong direction from step one. The most consequential error is **zero-sum bias**: the tendency to perceive non-zero-sum situations as zero-sum.\n\nNeighbor skills: use `prisoners-dilemma` when confirmed non-zero-sum but cooperation keeps failing. Use `strategic-commitment` when genuinely zero-sum and you need credible deterrence. Use `nash-equilibrium` for the equilibrium solution in confirmed zero-sum settings.\n\n## When to Use\n\nApply this skill when: entering a competitive situation before determining whether total value is fixed; someone proposes a negotiation assuming \"what I gain, you lose\"; a market entry hinges on whether total market size is fixed; a policy analysis needs to assess whether an intervention redistributes or creates welfare; someone uses zero-sum language (\"winner-take-all\", \"race to the bottom\", \"fixed pie\"); or someone frames the AI race, AI capex/compute buildout, AI-talent competition, or AI-native market entry as a single winner-take-all contest and you need to separate the genuinely fixed inputs (near-term compute/talent) from the growing pie (AI-driven productivity and adoption).\n\n**When NOT to use:** already confirmed zero-sum — go straight to minimax; clear cooperative surplus with no competitive distribution problem; stakes trivial and reversible; question already at equilibrium level — use `nash-equilibrium` directly.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** user has a concrete case → run The Process directly.\n- **Coach mode:** user is unfamiliar or has no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. **One-line what-it-is.** Zero-sum: total value fixed — if I get more, you get less by exactly the same amount. Most real-world competition is NOT zero-sum. The diagnosis changes everything about strategy.\n2. **Check fit.** Is the resource at stake genuinely fixed? If the total can change through cooperation, innovation, or trade, it is likely non-zero-sum.\n3. **Elicit the real case.** Get the specific situation — which market, which negotiation, which policy.\n> **[WAIT — do not advance until user responds]**\n4. **One step at a time.** Walk through the Diagnosis one question per turn. Start with: \"What exactly is being contested — and is the total amount of it fixed?\"\n> **[WAIT — do not advance until user responds]**\n5. **Close by naming the payoff.** State whether zero-sum or not, and what that means for strategy — cooperate/expand vs. minimax/capture.\n> **[WAIT — do not advance until user responds]**\n\n## The Process\n\nRun the **Zero-Sum Diagnosis**. Five gates; confirm or rule out at each one.\n\n1. **Define the contested resource.** State precisely what is being competed over (market share, license, price spread, votes, contract). If you cannot name a concrete unit being divided, the zero-sum frame likely does not apply.\n2. **Test fixity.** Can *innovation/technology* expand the total? Can *cooperation* create additional value? Can *time* change the total? If any answer is \"yes,\" the situation is non-zero-sum in that dimension.\n3. **Check for zero-sum bias.** Are you perceiving zero-sum because the resource is countable? Anchored on relative position over absolute gains? Ignoring comparative advantage? If expansion is feasible, you are in the wrong game.\n4. **If confirmed zero-sum: apply minimax.** Enumerate strategies and worst-case payoffs; choose the strategy maximizing your minimum; consider mixed strategies to prevent exploitation.\n5. **If confirmed non-zero-sum: design for cooperative surplus.** Quantify value neither party gets under pure competition. Specify the mechanism (contract, JV, standard, platform) to capture it. **Stop-rule:** if you cannot identify a concrete pie-growth mechanism, revert to zero-sum analysis.\n6. **State the time horizon.** Many situations are zero-sum short-term and non-zero-sum long-term. State both frames explicitly.\n\n### Output template\n\n```\nZero-Sum Diagnosis: \nContested resource: \nFixity test: innovation | cooperation | time \nBias audit: countability | relative-position | comparative-advantage ignored \nDiagnosis: — confidence \nIf zero-sum → minimax choice: | mixed-strategy consideration: \nIf non-zero-sum → surplus: | mechanism: | structure: \nStrategic recommendation: \n```\n\n*→ Method in Action: [Von Neumann and the Foundation of Zero-Sum Analysis — RAND, 1944–1950](examples/von-neumann-rand-1944-1950.md) · [The Smoot-Hawley Tariff (1930–1934)](examples/smoot-hawley-tariff-1930.md)*\n*→ 2026 lens: [Where the AI Race Is Zero-Sum and Where It Isn't (2024–2026)](examples/ai-competition-fixed-vs-growing-pie-2024-2026.md)*\n\n## Game-Type Packs\n\n- **Financial Derivatives:** Zero-sum by contract — every dollar the long gains, the short loses. Minimax applies; cooperation with counterparties is structurally impossible.\n- **Market Share Competition:** Constant-sum short-term; non-zero-sum long-term (category growth, platform effects). Treating long-term markets as zero-sum causes destructive price wars.\n- **Licensing/Spectrum Auctions:** Zero-sum by design — fixed license count. Firms that bid cooperatively lose to rivals who bid to win.\n- **Trade and International Economics:** Non-zero-sum — comparative advantage produces mutual gains. \"Trade deficits = losses\" is an analytical error.\n\n## Applying It Well\n\n- Always state the contested resource precisely before diagnosing — \"competition\" is not a resource.\n- Confirm the time horizon: the same situation can be zero-sum this quarter and non-zero-sum over three years.\n- Non-zero-sum surplus must be *captured*, not just identified — without a credible mechanism it stays theoretical.\n- Zero-sum bias is strongest when resources are countable and socially salient (share rankings, polls). Build in a deliberate check before decisions driven by competitive intel.\n\n*→ Primary sources: [references/sources.md](references/sources.md)*\n\n## Common Rationalizations\n\n**[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.**\n\n| Fake move | Reality |\n|---|---|\n| [D] \"Our market share went down, so we lost\" | Share and value captured differ. If total market grew 50% and share fell 30%→25%, absolute revenue grew. |\n| [D] \"Trade deficits mean we're losing\" | Deficits in goods are offset by export of financial claims. Comparative advantage shows both parties gain. |\n| [D] \"They won the contract, so we lost it\" | One award is zero-sum among bidders. Total industry contracting volume is usually not fixed. |\n| [D] \"We should cooperate — there's value to be created\" | Only correct if non-zero-sum. In genuine zero-sum settings, \"cooperation\" is illegal or a strategic error. |\n| [D] \"It's just market share — zero-sum by definition\" | Market share is a ratio. The denominator is not fixed unless you freeze the time horizon. |\n| [D] \"They made money, so we left money on the table\" | In non-zero-sum negotiation both parties can gain. Counterparty's gain implies your loss only if truly zero-sum. |\n| [D] \"Race to the bottom on price — classic zero-sum\" | Zero-sum on margin within a fixed pool, but non-zero-sum if lower prices expand total demand. |\n| [D] \"My industry experience says it's zero-sum\" | Intuitions fail at inflection points. Run diagnosis from first principles on the current structure. |\n| *→ Add [O] entries here after each real use — paste the actual failure pattern* | *What went wrong and why* |\n\n## Red Flags\n\n- Contested resource never explicitly named or tested for fixity\n- \"Zero-sum\" concluded because competition *feels* intense, not from resource structure\n- Non-zero-sum used to justify cooperation without identifying a concrete surplus-capture mechanism\n- Time horizon not specified — \"zero-sum\" treated as time-invariant\n- Zero-sum bias not audited (countability, relative position, comparative advantage)\n- Minimax applied to a non-zero-sum situation; or cooperation proposed in a genuinely zero-sum situation\n\n## Verification\n\n- [ ] Contested resource named precisely with the specific unit being divided\n- [ ] Fixity test run on all three dimensions: technology, cooperation, time horizon\n- [ ] Zero-sum bias audited: countability, relative-position anchoring, comparative-advantage blindness\n- [ ] Diagnosis states game type with reasoning; time horizon specified for both short and long term\n- [ ] If zero-sum: minimax strategy identified including mixed-strategy consideration\n- [ ] If non-zero-sum: surplus estimated, mechanism named, structural capture mechanism proposed\n- [ ] Stop-rule applied: non-zero-sum confirmed by identifiable mechanism, not assumed from desire to cooperate\n\n---\n\n*Part of **deciqAI Knowledge Skills** — 227 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. **See it run → https://www.deciqai.com/c/zero-sum-game** · ⭐ Star the repo → https://github.com/deciqAI/knowledge-skills · Contributions welcome.*\n\n*Agents: latest version & machine-readable metadata → https://www.deciqai.com/s/zero-sum-game.json*\n\nFile v1.0.6:_meta.json\n\n{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"zero-sum-game\",\n \"version\": \"1.0.6\",\n \"publishedAt\": 1784226147731\n}\n\nFile v1.0.6:references/sources.md\n\n# Sources — zero-sum-game\n\n> *Primary sources for the [zero-sum-game](../SKILL.md) skill.*\n\n- Von Neumann, J. & Morgenstern, O. (1944). *Theory of Games and Economic Behavior.* Princeton University Press. The founding text of game theory; contains the Minimax Theorem and the formal definition of zero-sum games. Reprint available via Princeton University Press. https://press.princeton.edu/books/paperback/9780691130613/theory-of-games-and-economic-behavior\n- Schelling, T.C. (1960). *The Strategy of Conflict.* Harvard University Press. The canonical analysis of zero-sum vs. non-zero-sum conflict in negotiation and deterrence, including the Cold War application. https://www.hup.harvard.edu/books/9780674840317\n- Nash, J. F. (1950). \"Equilibrium Points in n-Person Games.\" *Proceedings of the National Academy of Sciences*, 36(1), pp. 48–49. The equilibrium concept that generalizes beyond zero-sum settings; for zero-sum games, Nash equilibrium coincides with minimax. https://doi.org/10.1073/pnas.36.1.48\n- Meegan, D.V. (2010). \"Zero-Sum Bias: Perceived Competition Despite Unlimited Resources.\" *Frontiers in Psychology*, 1, 191. Primary empirical documentation of zero-sum bias as a cognitive phenomenon — the systematic tendency to perceive zero-sum structures when they are not present. https://doi.org/10.3389/fpsyg.2010.00191\n- Dixit, A. & Nalebuff, B. (1991). *Thinking Strategically.* W.W. Norton. The standard practical treatment of zero-sum vs. non-zero-sum games for practitioners; Chapter 4 covers the distinction in business contexts. ISBN 978-0393310351.\n- Irwin, D.A. (2011). *Peddling Protectionism: Smoot-Hawley and the Great Depression.* Princeton University Press. The definitive historical account of the 1930 tariff — the political economy of its passage, the foreign retaliation it provoked, and its role in the collapse and fragmentation of world trade; the canonical documented case of zero-sum misdiagnosis in trade policy. ISBN 978-0691150321.\n\n- International Energy Agency (2025). *Energy and AI* (World Energy Outlook Special Report), published April 2025. IEA, Paris. Documents the 2024–2025 scale-up of AI compute and data-center demand, and the physical constraints (power, hardware supply, lead times) that bound near-term capacity — useful for grounding the \"near-term compute is a fixed input\" side of the AI zero-sum diagnosis. https://www.iea.org/reports/energy-and-ai\n- Stanford HAI (2025). *Artificial Intelligence Index Report 2025,* published April 2025. Stanford Institute for Human-Centered AI. Tracks model performance, investment, adoption, and compute trends through 2024 — the widely cited public baseline for the state of AI competition, capital expenditure, and the concentration of frontier capability and talent. https://hai.stanford.edu/ai-index/2025-ai-index-report\n\n**What is not cited and why:** Popular business writing frequently attributes the phrase \"zero-sum game\" to competitive strategy without checking whether the specific situation meets the mathematical definition. Claims that \"competition is always zero-sum\" or \"negotiation is always zero-sum\" are asserted but unverified. This skill uses the mathematical definition from Von Neumann and Morgenstern as the anchor, not intuitive usage.\n\nFile v1.0.6:examples/ai-competition-fixed-vs-growing-pie-2024-2026.md\n\n# Method in Action: Where the AI Race Is Zero-Sum and Where It Isn't (2024–2026)\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nBy 2024–2026 the dominant framing of the AI boom was a single \"race\" — one leaderboard, one winner, everyone else loses. That framing quietly bundles together resources with very different structures. Some inputs to AI are genuinely fixed in the near term and therefore zero-sum; the output — AI-driven productivity — is not. Treating the whole thing as one zero-sum contest is exactly the diagnosis error this skill is built to catch: it pushes firms toward pure capture (outbid rivals, hoard talent, block competitors) when part of the game rewards expansion (build the market, enlarge supply, complement rather than substitute).\n\nThe point of the diagnosis is that \"the AI race\" is not one game — it is a **mixed** game, and you have to name the resource before you know which move applies.\n\nRunning the Diagnosis:\n\n**Step 1 (define the contested resource).** Split \"AI competition\" into its distinct contested resources rather than treating it as one blob:\n- *Near-term advanced-chip and high-bandwidth-memory (HBM) supply* — the units of leading-edge accelerators and the HBM stacks they require, buildable only through a small number of suppliers with long lead times.\n- *Top-tier AI research talent* — the small pool of people who have actually trained frontier systems.\n- *AI-driven productivity / the value AI creates for end users* — the output the whole boom is ostensibly about.\n\nEach is a nameable, distinct unit. That is the precondition for a real diagnosis; \"who wins AI\" is not a resource.\n\n**Step 2 (test fixity) — run separately per resource:**\n- *Chips/HBM, near term:* **fixed.** Leading-edge fabrication and advanced-memory capacity cannot be expanded on a quarterly horizon — it is gated by a handful of suppliers and multi-year fab and packaging build-outs. Within a given year, one buyer's allocation is largely another's shortfall. **Zero-sum (near term).**\n- *Top talent, near term:* **fixed.** The pool of people who have led frontier training runs is small and slow to grow. A senior hire at one lab is, for that cycle, a hire the rival did not get. **Zero-sum (near term).**\n- *AI productivity / end-user value:* **not fixed.** Cooperation and innovation expand it — better models, cheaper inference, and new applications enlarge total value created rather than merely reallocating it. One firm shipping a useful AI product does not consume the possibility of another firm shipping one. **Non-zero-sum.**\n- *Time dimension:* the fixity of chips and talent is a **near-term** property. Over a multi-year horizon, supply responds — new fab and advanced-packaging capacity comes online and the trained-talent pool grows — so even these resources become less zero-sum the longer the horizon.\n\n**Step 3 (check for zero-sum bias).** The popular \"one race, one winner\" frame shows all three bias markers on the *productivity* dimension:\n- *Countability:* leaderboard ranks, benchmark scores, model-release dates, and capex figures are countable and salient, so attention anchors on the visibly rankable inputs and treats the diffuse, expandable productivity pie as if it were another leaderboard.\n- *Relative-position anchoring:* \"we must be #1 or we lose\" fixates on rank rather than on absolute value created — a firm can rank second and still capture a growing absolute business if the pie is expanding.\n- *Comparative-advantage blindness:* the frame ignores that different players can specialize (chips, cloud, foundation models, applications, tooling) and gain jointly, treating any rival's success as one's own loss.\n\nSo the diagnosis splits: **bias is present on the productivity dimension, absent on the chip and talent dimensions** — those really are fixed near-term.\n\n**Step 4 (confirmed-zero-sum branch → minimax) for chips and talent, near term.** Where the resource is genuinely fixed, capture logic is correct, not a bias. For scarce near-term compute the rational move is to secure allocation against the worst case — long-term supply commitments, pre-purchase and reserved capacity, supplier diversification, and vertical moves toward custom silicon so a rival's buying spree cannot starve you. For scarce talent, competitive retention and acquisition are appropriate. This is the minimax posture: choose the strategy that protects your floor against a rival who is trying to lock up the same fixed pool. Cooperation here does not create a bigger pool this year, so \"let's not compete\" would be a strategic error on this dimension.\n\n**Step 5 (confirmed-non-zero-sum branch → design for surplus) for the productivity pie.** On the output dimension the correct move is expansion, not capture. The surplus is the value AI creates that no single firm captures under pure rivalry — new categories of application, workflows automated, users served. The **mechanisms** to capture it are concrete and already visible in this period: open ecosystems and platforms (API access, model marketplaces, developer tooling), interoperability and shared standards, and complement strategies (a cloud provider and a model lab enlarging each other's markets rather than only fighting for rank). *Stop-rule check:* this is not wishful cooperation talk — the pie-growth mechanism is nameable (falling inference cost and new applications enlarging total AI usage), so the non-zero-sum diagnosis holds rather than reverting to capture.\n\n**Step 6 (state the time horizon).** State both frames explicitly. *Near term:* chips/HBM and top talent are fixed → zero-sum → capture and minimax are correct on those inputs. *Longer term:* supply and the talent pool respond, and the productivity pie keeps growing → the game shifts toward non-zero-sum → the firms that also invested in market-expanding, complement-building strategy win the larger absolute prize. Mistaking the near-term fixed inputs for a permanently fixed *whole* is the error: it justifies burning resources purely to deny rivals while under-investing in the expansion that determines the long-run size of the business.\n\nThe mapped steps:\n1. Contested resource: split into near-term chips/HBM, top talent, and AI productivity — three different units, not one \"race\"\n2. Fixity test: chips fixed (near term), talent fixed (near term), productivity not fixed; all soften over a longer horizon\n3. Bias audit: countability, relative-position, and comparative-advantage blindness all present on the productivity dimension; absent on the fixed-input dimensions\n4. Zero-sum branch: secure fixed compute and talent via supply commitments and retention — minimax capture is correct there\n5. Non-zero-sum branch: expand the productivity pie via platforms, interoperability, and complement strategies — surplus with a named mechanism\n6. Horizon: zero-sum near term on inputs, non-zero-sum longer term and on output — state both, and don't let the first justify neglecting the second\n\n**Diagnosis: Mixed** — genuinely zero-sum on near-term compute and talent, non-zero-sum on the AI-productivity pie. The strategic failure mode of the era is applying a single frame to a mixed game.\n\n*Sources: Von Neumann, J. & Morgenstern, O. (1944), Theory of Games and Economic Behavior, Princeton University Press (definition of zero-sum games and the minimax result); Meegan, D.V. (2010), \"Zero-Sum Bias: Perceived Competition Despite Unlimited Resources,\" Frontiers in Psychology, 1:191 (empirical basis for zero-sum bias). The 2024–2026 characterization of constrained leading-edge AI accelerator and high-bandwidth-memory supply, and of a small frontier-talent pool, reflects widely reported industry conditions during that period; specific allocation figures are omitted deliberately.*\n\nFile v1.0.6:examples/smoot-hawley-tariff-1930.md\n\n# Method in Action: The Smoot-Hawley Tariff and the Fixed-Pie Fallacy in Trade (1930–1934)\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nThe Smoot-Hawley Tariff Act of 1930 is the most consequential documented case of zero-sum misdiagnosis in economic policy — a strategy built on the assumption that trade is a fixed pie, executed at national scale, with measurable results.\n\nThe implicit diagnosis behind the tariff: imports capture American production and jobs, so every unit of imports blocked is a unit of domestic output gained. On this logic, Congress raised duties on over 20,000 imported goods, and President Hoover signed the act in June 1930 — over a petition signed by more than a thousand economists urging a veto. The economists' objection was precisely a zero-sum objection: trade is mutual gain via comparative advantage, and blocking it destroys value on both sides rather than transferring it.\n\nRunning the Diagnosis on the 1930 decision:\n\n**Step 1 (contested resource):** Domestic production and employment in import-competing sectors. Nameable and countable — which is exactly the condition under which zero-sum bias is strongest.\n\n**Step 2 (fixity test):** Fails on all three dimensions. *Cooperation:* trade itself is the cooperative mechanism — specialization by comparative advantage makes total output larger than under autarky, so the \"pie\" of production is not fixed. *Innovation/technology:* export industries expand when trading partners prosper. *Time:* even if a tariff transfers demand to domestic producers this quarter, retaliation and shrinking foreign incomes cut export demand over the following years.\n\n**Step 3 (bias audit):** All three bias markers present. Countability — imports arrive in visible, countable units at ports, while the diffuse gains from trade do not. Relative-position anchoring — the political debate framed foreign producers' sales as America's losses. Comparative-advantage blindness — the analysis treated a dollar of imports as a dollar of forgone domestic production, ignoring that both sides gain from specialization.\n\n**Step 4/5 (what the wrong diagnosis produced):** Because policymakers treated a non-zero-sum game as zero-sum, they played capture instead of designing for surplus. Trading partners ran the same wrong playbook in reverse: Canada — the largest US trading partner — retaliated with duties targeting US exports, and other countries followed with tariffs, quotas, and preferential blocs. Both moves were individually \"rational\" under the fixed-pie frame and collectively destructive outside it. Between 1929 and 1933 world trade collapsed to a fraction of its former volume; the Depression drove much of the fall, but as Irwin documents, the tariff and the retaliation it provoked deepened the contraction and fragmented the world trading system into discriminatory blocs. The pie did not get redivided — it shrank for everyone.\n\n**The corrected diagnosis:** The reversal came only when the game was reframed. The Reciprocal Trade Agreements Act of 1934 abandoned unilateral capture for negotiated mutual tariff reduction — an explicit surplus-capture mechanism (bilateral agreements, later generalized into GATT in 1947). Same players, same \"contested\" trade flows; the strategy flipped from minimax-style protection to cooperative expansion once the non-zero-sum structure was recognized, and postwar trade grew for decades under that frame.\n\n**Stop-rule check:** The non-zero-sum diagnosis here is not wishful cooperation talk — the pie-growth mechanism is concrete (comparative advantage, formalized in reciprocal agreements) and its removal in 1930–1933 produced the predicted mutual loss.\n\nThe mapped steps:\n1. Contested resource: domestic production and jobs in import-competing sectors — countable, hence bias-prone\n2. Fixity test: fails on cooperation (comparative advantage), technology (export growth), and time (retaliation lag) — non-zero-sum\n3. Bias audit: countability, relative-position anchoring, and comparative-advantage blindness all present in the 1930 debate\n4. Wrong-frame consequence: capture strategy triggered retaliatory capture; world trade contracted — mutual loss, not transfer\n5. Corrected strategy: RTAA 1934 → GATT 1947 — a named mechanism converting the game back to cooperative surplus\n\nPrimary source: Irwin, D.A. (2011). *Peddling Protectionism: Smoot-Hawley and the Great Depression.* Princeton University Press.\n\nFile v1.0.6:examples/von-neumann-rand-1944-1950.md\n\n# Method in Action: Von Neumann and the Foundation of Zero-Sum Analysis — RAND, 1944–1950\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nThe zero-sum framework did not originate as a business tool. It was developed to analyze nuclear deterrence.\n\nIn 1944, John von Neumann and Oskar Morgenstern published *Theory of Games and Economic Behavior*, establishing the mathematical foundation of game theory. Their central result for zero-sum games — the Minimax Theorem — had been proved by von Neumann in 1928: in any finite two-person zero-sum game, there exists a mixed-strategy pair such that neither player can improve their expected payoff by unilaterally deviating. The equilibrium payoff to each player is simultaneously the maximum of their minimum guarantee and the minimum of their maximum loss.\n\nBy 1950, RAND Corporation — the primary Cold War strategy think tank — was applying this framework to nuclear deterrence. The core question: is nuclear confrontation between the United States and USSR a zero-sum game? If yes, the minimax solution determines rational deterrence posture. If no — if both parties are worse off under nuclear exchange than under mutual restraint — the situation is a non-zero-sum game requiring a different analysis.\n\nRunning the Diagnosis on Cold War nuclear strategy:\n\n**Step 1 (contested resource):** Global political influence, territorial control, and the absence of nuclear exchange.\n\n**Step 2 (fixity test):** Political influence was partially zero-sum (Soviet gains in Europe meant Western losses). But the *survival of both nations* was non-zero-sum — nuclear exchange destroyed value for both sides simultaneously. Total welfare was not fixed: mutual restraint produced more total survival than mutual escalation.\n\n**Step 3 (bias audit):** Early Cold War strategists committed a countability error — they focused on the zero-sum dimension (territory, influence) and neglected the non-zero-sum dimension (mutual destruction). Schelling's *Strategy of Conflict* (1960) corrected this, showing that the deterrence game was fundamentally non-zero-sum because mutual destruction was the worst outcome for *both* players.\n\n**Step 4/5 (strategy):** Because the game was non-zero-sum, the correct strategy was not minimax but the design of *credible commitment devices* — each side needed to credibly commit to *not* launching a first strike in exchange for reciprocal restraint. Mutual Assured Destruction (MAD) was not a minimax strategy; it was a cooperative equilibrium sustained by credible commitment mechanisms (second-strike capability, hotlines, arms-control treaties).\n\n**Stop-rule applied:** The zero-sum diagnosis was limited to the political dimension. When strategists extended zero-sum reasoning to the nuclear dimension, they produced strategies (first-strike advantages, counterforce targeting) that the non-zero-sum structure showed were collectively irrational. The diagnosis prevented the most dangerous errors.\n\nPrimary sources: Von Neumann, J. & Morgenstern, O. (1944), *Theory of Games and Economic Behavior*, Princeton University Press; Schelling, T.C. (1960), *The Strategy of Conflict*, Harvard University Press.\n\nFile v1.0.6:skill-card.md\n\n## Description:\n\nHelps agents diagnose whether a negotiation, market, policy, or competitive situation is truly zero-sum before recommending minimax, cooperation, or mixed strategy.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[deciqai](https://clawhub.ai/user/deciqai)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nExternal users, developers, and strategy analysts use this skill to test whether a contested resource is fixed, audit zero-sum bias, and choose an appropriate strategic posture for competition, negotiation, market, policy, or AI race scenarios.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: The skill can produce strategic, business, policy, financial, legal, or operational recommendations that may be incorrect or incomplete for a real-world decision.\n\nMitigation: Treat outputs as advisory analysis and require qualified human review before using them to approve competitive, financial, legal, policy, or operational actions.\n\nRisk: A user may apply a zero-sum frame to a situation where total value can grow, shrink, or vary over time.\n\nMitigation: Use the skill's fixity test, zero-sum bias audit, and time-horizon check before acting on minimax or capture-oriented recommendations.\n\nRisk: The skill may recommend cooperation or surplus capture without a concrete mechanism.\n\nMitigation: Apply the documented stop rule: if no concrete pie-growth or surplus-capture mechanism is identified, revert to zero-sum analysis or request more context.\n\n## Reference(s):\n\n- [ClawHub Skill Page](https://clawhub.ai/deciqai/skills/zero-sum-game)\n- [Primary Sources](references/sources.md)\n- [Von Neumann and the Foundation of Zero-Sum Analysis](examples/von-neumann-rand-1944-1950.md)\n- [The Smoot-Hawley Tariff](examples/smoot-hawley-tariff-1930.md)\n- [Where the AI Race Is Zero-Sum and Where It Isn't](examples/ai-competition-fixed-vs-growing-pie-2024-2026.md)\n- [Theory of Games and Economic Behavior](https://press.princeton.edu/books/paperback/9780691130613/theory-of-games-and-economic-behavior)\n- [The Strategy of Conflict](https://www.hup.harvard.edu/books/9780674840317)\n- [Equilibrium Points in N-Person Games](https://doi.org/10.1073/pnas.36.1.48)\n- [Zero-Sum Bias](https://doi.org/10.3389/fpsyg.2010.00191)\n- [Energy and AI](https://www.iea.org/reports/energy-and-ai)\n- [Artificial Intelligence Index Report 2025](https://hai.stanford.edu/ai-index/2025-ai-index-report)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, guidance]\n\n**Output Format:** [Markdown diagnosis with structured fields and a recommendation paragraph]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [May ask one question at a time in coach mode before producing a diagnosis.]\n\n## Skill Version(s):\n\n1.0.6 (source: server release evidence)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nArchive v1.0.5: 7 files, 16022 bytes\n\nFiles: examples/ai-competition-fixed-vs-growing-pie-2024-2026.md (7842b), examples/smoot-hawley-tariff-1930.md (4482b), examples/von-neumann-rand-1944-1950.md (3207b), references/sources.md (3275b), skill-card.md (3015b), SKILL.md (10257b), _meta.json (132b)\n\nFile v1.0.5:SKILL.md\n\n---\nname: zero-sum-game\ndescription: \"Activate when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', uses phrases like 'winner-take-all', 'race to the bottom', or 'your gain is my loss', or needs to check whether a negotiation/market/policy situation is truly zero-sum before designing strategy.\n Do NOT activate when: the situation is already confirmed zero-sum (chess, derivatives, fixed-license auctions) and diagnosis is complete — go straight to minimax; or the question is already framed at the equilibrium level — use nash-equilibrium directly.\"\n---\n\n# Zero-Sum Game\n\n## Overview\n\nZero-sum means total value is fixed — one player's gain is another's exact loss. Most real-world competition is NOT zero-sum: the pie can grow, shrink, or be split in many ways. Misdiagnosis sends strategy in the wrong direction from step one. The most consequential error is **zero-sum bias**: the tendency to perceive non-zero-sum situations as zero-sum.\n\nNeighbor skills: use `prisoners-dilemma` when confirmed non-zero-sum but cooperation keeps failing. Use `strategic-commitment` when genuinely zero-sum and you need credible deterrence. Use `nash-equilibrium` for the equilibrium solution in confirmed zero-sum settings.\n\n## When to Use\n\nApply this skill when: entering a competitive situation before determining whether total value is fixed; someone proposes a negotiation assuming \"what I gain, you lose\"; a market entry hinges on whether total market size is fixed; a policy analysis needs to assess whether an intervention redistributes or creates welfare; someone uses zero-sum language (\"winner-take-all\", \"race to the bottom\", \"fixed pie\"); or someone frames the AI race, AI capex/compute buildout, AI-talent competition, or AI-native market entry as a single winner-take-all contest and you need to separate the genuinely fixed inputs (near-term compute/talent) from the growing pie (AI-driven productivity and adoption).\n\n**When NOT to use:** already confirmed zero-sum — go straight to minimax; clear cooperative surplus with no competitive distribution problem; stakes trivial and reversible; question already at equilibrium level — use `nash-equilibrium` directly.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** user has a concrete case → run The Process directly.\n- **Coach mode:** user is unfamiliar or has no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. **One-line what-it-is.** Zero-sum: total value fixed — if I get more, you get less by exactly the same amount. Most real-world competition is NOT zero-sum. The diagnosis changes everything about strategy.\n2. **Check fit.** Is the resource at stake genuinely fixed? If the total can change through cooperation, innovation, or trade, it is likely non-zero-sum.\n3. **Elicit the real case.** Get the specific situation — which market, which negotiation, which policy.\n> **[WAIT — do not advance until user responds]**\n4. **One step at a time.** Walk through the Diagnosis one question per turn. Start with: \"What exactly is being contested — and is the total amount of it fixed?\"\n> **[WAIT — do not advance until user responds]**\n5. **Close by naming the payoff.** State whether zero-sum or not, and what that means for strategy — cooperate/expand vs. minimax/capture.\n> **[WAIT — do not advance until user responds]**\n\n## The Process\n\nRun the **Zero-Sum Diagnosis**. Five gates; confirm or rule out at each one.\n\n1. **Define the contested resource.** State precisely what is being competed over (market share, license, price spread, votes, contract). If you cannot name a concrete unit being divided, the zero-sum frame likely does not apply.\n2. **Test fixity.** Can *innovation/technology* expand the total? Can *cooperation* create additional value? Can *time* change the total? If any answer is \"yes,\" the situation is non-zero-sum in that dimension.\n3. **Check for zero-sum bias.** Are you perceiving zero-sum because the resource is countable? Anchored on relative position over absolute gains? Ignoring comparative advantage? If expansion is feasible, you are in the wrong game.\n4. **If confirmed zero-sum: apply minimax.** Enumerate strategies and worst-case payoffs; choose the strategy maximizing your minimum; consider mixed strategies to prevent exploitation.\n5. **If confirmed non-zero-sum: design for cooperative surplus.** Quantify value neither party gets under pure competition. Specify the mechanism (contract, JV, standard, platform) to capture it. **Stop-rule:** if you cannot identify a concrete pie-growth mechanism, revert to zero-sum analysis.\n6. **State the time horizon.** Many situations are zero-sum short-term and non-zero-sum long-term. State both frames explicitly.\n\n### Output template\n\n```\nZero-Sum Diagnosis: \nContested resource: \nFixity test: innovation | cooperation | time \nBias audit: countability | relative-position | comparative-advantage ignored \nDiagnosis: — confidence \nIf zero-sum → minimax choice: | mixed-strategy consideration: \nIf non-zero-sum → surplus: | mechanism: | structure: \nStrategic recommendation: \n```\n\n*→ Method in Action: [Von Neumann and the Foundation of Zero-Sum Analysis — RAND, 1944–1950](examples/von-neumann-rand-1944-1950.md) · [The Smoot-Hawley Tariff (1930–1934)](examples/smoot-hawley-tariff-1930.md)*\n*→ 2026 lens: [Where the AI Race Is Zero-Sum and Where It Isn't (2024–2026)](examples/ai-competition-fixed-vs-growing-pie-2024-2026.md)*\n\n## Game-Type Packs\n\n- **Financial Derivatives:** Zero-sum by contract — every dollar the long gains, the short loses. Minimax applies; cooperation with counterparties is structurally impossible.\n- **Market Share Competition:** Constant-sum short-term; non-zero-sum long-term (category growth, platform effects). Treating long-term markets as zero-sum causes destructive price wars.\n- **Licensing/Spectrum Auctions:** Zero-sum by design — fixed license count. Firms that bid cooperatively lose to rivals who bid to win.\n- **Trade and International Economics:** Non-zero-sum — comparative advantage produces mutual gains. \"Trade deficits = losses\" is an analytical error.\n\n## Applying It Well\n\n- Always state the contested resource precisely before diagnosing — \"competition\" is not a resource.\n- Confirm the time horizon: the same situation can be zero-sum this quarter and non-zero-sum over three years.\n- Non-zero-sum surplus must be *captured*, not just identified — without a credible mechanism it stays theoretical.\n- Zero-sum bias is strongest when resources are countable and socially salient (share rankings, polls). Build in a deliberate check before decisions driven by competitive intel.\n\n*→ Primary sources: [references/sources.md](references/sources.md)*\n\n## Common Rationalizations\n\n**[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.**\n\n| Fake move | Reality |\n|---|---|\n| [D] \"Our market share went down, so we lost\" | Share and value captured differ. If total market grew 50% and share fell 30%→25%, absolute revenue grew. |\n| [D] \"Trade deficits mean we're losing\" | Deficits in goods are offset by export of financial claims. Comparative advantage shows both parties gain. |\n| [D] \"They won the contract, so we lost it\" | One award is zero-sum among bidders. Total industry contracting volume is usually not fixed. |\n| [D] \"We should cooperate — there's value to be created\" | Only correct if non-zero-sum. In genuine zero-sum settings, \"cooperation\" is illegal or a strategic error. |\n| [D] \"It's just market share — zero-sum by definition\" | Market share is a ratio. The denominator is not fixed unless you freeze the time horizon. |\n| [D] \"They made money, so we left money on the table\" | In non-zero-sum negotiation both parties can gain. Counterparty's gain implies your loss only if truly zero-sum. |\n| [D] \"Race to the bottom on price — classic zero-sum\" | Zero-sum on margin within a fixed pool, but non-zero-sum if lower prices expand total demand. |\n| [D] \"My industry experience says it's zero-sum\" | Intuitions fail at inflection points. Run diagnosis from first principles on the current structure. |\n| *→ Add [O] entries here after each real use — paste the actual failure pattern* | *What went wrong and why* |\n\n## Red Flags\n\n- Contested resource never explicitly named or tested for fixity\n- \"Zero-sum\" concluded because competition *feels* intense, not from resource structure\n- Non-zero-sum used to justify cooperation without identifying a concrete surplus-capture mechanism\n- Time horizon not specified — \"zero-sum\" treated as time-invariant\n- Zero-sum bias not audited (countability, relative position, comparative advantage)\n- Minimax applied to a non-zero-sum situation; or cooperation proposed in a genuinely zero-sum situation\n\n## Verification\n\n- [ ] Contested resource named precisely with the specific unit being divided\n- [ ] Fixity test run on all three dimensions: technology, cooperation, time horizon\n- [ ] Zero-sum bias audited: countability, relative-position anchoring, comparative-advantage blindness\n- [ ] Diagnosis states game type with reasoning; time horizon specified for both short and long term\n- [ ] If zero-sum: minimax strategy identified including mixed-strategy consideration\n- [ ] If non-zero-sum: surplus estimated, mechanism named, structural capture mechanism proposed\n- [ ] Stop-rule applied: non-zero-sum confirmed by identifiable mechanism, not assumed from desire to cooperate\n\n---\n\n*Part of **deciqAI Knowledge Skills** — 189 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. **See it run → https://www.deciqai.com/c/zero-sum-game** · ⭐ Star the repo → https://github.com/deciqAI/knowledge-skills · Contributions welcome.*\n\nFile v1.0.5:_meta.json\n\n{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"zero-sum-game\",\n \"version\": \"1.0.5\",\n \"publishedAt\": 1783596178435\n}\n\nFile v1.0.5:references/sources.md\n\n# Sources — zero-sum-game\n\n> *Primary sources for the [zero-sum-game](../SKILL.md) skill.*\n\n- Von Neumann, J. & Morgenstern, O. (1944). *Theory of Games and Economic Behavior.* Princeton University Press. The founding text of game theory; contains the Minimax Theorem and the formal definition of zero-sum games. Reprint available via Princeton University Press. https://press.princeton.edu/books/paperback/9780691130613/theory-of-games-and-economic-behavior\n- Schelling, T.C. (1960). *The Strategy of Conflict.* Harvard University Press. The canonical analysis of zero-sum vs. non-zero-sum conflict in negotiation and deterrence, including the Cold War application. https://www.hup.harvard.edu/books/9780674840317\n- Nash, J. F. (1950). \"Equilibrium Points in n-Person Games.\" *Proceedings of the National Academy of Sciences*, 36(1), pp. 48–49. The equilibrium concept that generalizes beyond zero-sum settings; for zero-sum games, Nash equilibrium coincides with minimax. https://doi.org/10.1073/pnas.36.1.48\n- Meegan, D.V. (2010). \"Zero-Sum Bias: Perceived Competition Despite Unlimited Resources.\" *Frontiers in Psychology*, 1, 191. Primary empirical documentation of zero-sum bias as a cognitive phenomenon — the systematic tendency to perceive zero-sum structures when they are not present. https://doi.org/10.3389/fpsyg.2010.00191\n- Dixit, A. & Nalebuff, B. (1991). *Thinking Strategically.* W.W. Norton. The standard practical treatment of zero-sum vs. non-zero-sum games for practitioners; Chapter 4 covers the distinction in business contexts. ISBN 978-0393310351.\n- Irwin, D.A. (2011). *Peddling Protectionism: Smoot-Hawley and the Great Depression.* Princeton University Press. The definitive historical account of the 1930 tariff — the political economy of its passage, the foreign retaliation it provoked, and its role in the collapse and fragmentation of world trade; the canonical documented case of zero-sum misdiagnosis in trade policy. ISBN 978-0691150321.\n\n- International Energy Agency (2025). *Energy and AI* (World Energy Outlook Special Report), published April 2025. IEA, Paris. Documents the 2024–2025 scale-up of AI compute and data-center demand, and the physical constraints (power, hardware supply, lead times) that bound near-term capacity — useful for grounding the \"near-term compute is a fixed input\" side of the AI zero-sum diagnosis. https://www.iea.org/reports/energy-and-ai\n- Stanford HAI (2025). *Artificial Intelligence Index Report 2025,* published April 2025. Stanford Institute for Human-Centered AI. Tracks model performance, investment, adoption, and compute trends through 2024 — the widely cited public baseline for the state of AI competition, capital expenditure, and the concentration of frontier capability and talent. https://hai.stanford.edu/ai-index/2025-ai-index-report\n\n**What is not cited and why:** Popular business writing frequently attributes the phrase \"zero-sum game\" to competitive strategy without checking whether the specific situation meets the mathematical definition. Claims that \"competition is always zero-sum\" or \"negotiation is always zero-sum\" are asserted but unverified. This skill uses the mathematical definition from Von Neumann and Morgenstern as the anchor, not intuitive usage.\n\nFile v1.0.5:examples/ai-competition-fixed-vs-growing-pie-2024-2026.md\n\n# Method in Action: Where the AI Race Is Zero-Sum and Where It Isn't (2024–2026)\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nBy 2024–2026 the dominant framing of the AI boom was a single \"race\" — one leaderboard, one winner, everyone else loses. That framing quietly bundles together resources with very different structures. Some inputs to AI are genuinely fixed in the near term and therefore zero-sum; the output — AI-driven productivity — is not. Treating the whole thing as one zero-sum contest is exactly the diagnosis error this skill is built to catch: it pushes firms toward pure capture (outbid rivals, hoard talent, block competitors) when part of the game rewards expansion (build the market, enlarge supply, complement rather than substitute).\n\nThe point of the diagnosis is that \"the AI race\" is not one game — it is a **mixed** game, and you have to name the resource before you know which move applies.\n\nRunning the Diagnosis:\n\n**Step 1 (define the contested resource).** Split \"AI competition\" into its distinct contested resources rather than treating it as one blob:\n- *Near-term advanced-chip and high-bandwidth-memory (HBM) supply* — the units of leading-edge accelerators and the HBM stacks they require, buildable only through a small number of suppliers with long lead times.\n- *Top-tier AI research talent* — the small pool of people who have actually trained frontier systems.\n- *AI-driven productivity / the value AI creates for end users* — the output the whole boom is ostensibly about.\n\nEach is a nameable, distinct unit. That is the precondition for a real diagnosis; \"who wins AI\" is not a resource.\n\n**Step 2 (test fixity) — run separately per resource:**\n- *Chips/HBM, near term:* **fixed.** Leading-edge fabrication and advanced-memory capacity cannot be expanded on a quarterly horizon — it is gated by a handful of suppliers and multi-year fab and packaging build-outs. Within a given year, one buyer's allocation is largely another's shortfall. **Zero-sum (near term).**\n- *Top talent, near term:* **fixed.** The pool of people who have led frontier training runs is small and slow to grow. A senior hire at one lab is, for that cycle, a hire the rival did not get. **Zero-sum (near term).**\n- *AI productivity / end-user value:* **not fixed.** Cooperation and innovation expand it — better models, cheaper inference, and new applications enlarge total value created rather than merely reallocating it. One firm shipping a useful AI product does not consume the possibility of another firm shipping one. **Non-zero-sum.**\n- *Time dimension:* the fixity of chips and talent is a **near-term** property. Over a multi-year horizon, supply responds — new fab and advanced-packaging capacity comes online and the trained-talent pool grows — so even these resources become less zero-sum the longer the horizon.\n\n**Step 3 (check for zero-sum bias).** The popular \"one race, one winner\" frame shows all three bias markers on the *productivity* dimension:\n- *Countability:* leaderboard ranks, benchmark scores, model-release dates, and capex figures are countable and salient, so attention anchors on the visibly rankable inputs and treats the diffuse, expandable productivity pie as if it were another leaderboard.\n- *Relative-position anchoring:* \"we must be #1 or we lose\" fixates on rank rather than on absolute value created — a firm can rank second and still capture a growing absolute business if the pie is expanding.\n- *Comparative-advantage blindness:* the frame ignores that different players can specialize (chips, cloud, foundation models, applications, tooling) and gain jointly, treating any rival's success as one's own loss.\n\nSo the diagnosis splits: **bias is present on the productivity dimension, absent on the chip and talent dimensions** — those really are fixed near-term.\n\n**Step 4 (confirmed-zero-sum branch → minimax) for chips and talent, near term.** Where the resource is genuinely fixed, capture logic is correct, not a bias. For scarce near-term compute the rational move is to secure allocation against the worst case — long-term supply commitments, pre-purchase and reserved capacity, supplier diversification, and vertical moves toward custom silicon so a rival's buying spree cannot starve you. For scarce talent, competitive retention and acquisition are appropriate. This is the minimax posture: choose the strategy that protects your floor against a rival who is trying to lock up the same fixed pool. Cooperation here does not create a bigger pool this year, so \"let's not compete\" would be a strategic error on this dimension.\n\n**Step 5 (confirmed-non-zero-sum branch → design for surplus) for the productivity pie.** On the output dimension the correct move is expansion, not capture. The surplus is the value AI creates that no single firm captures under pure rivalry — new categories of application, workflows automated, users served. The **mechanisms** to capture it are concrete and already visible in this period: open ecosystems and platforms (API access, model marketplaces, developer tooling), interoperability and shared standards, and complement strategies (a cloud provider and a model lab enlarging each other's markets rather than only fighting for rank). *Stop-rule check:* this is not wishful cooperation talk — the pie-growth mechanism is nameable (falling inference cost and new applications enlarging total AI usage), so the non-zero-sum diagnosis holds rather than reverting to capture.\n\n**Step 6 (state the time horizon).** State both frames explicitly. *Near term:* chips/HBM and top talent are fixed → zero-sum → capture and minimax are correct on those inputs. *Longer term:* supply and the talent pool respond, and the productivity pie keeps growing → the game shifts toward non-zero-sum → the firms that also invested in market-expanding, complement-building strategy win the larger absolute prize. Mistaking the near-term fixed inputs for a permanently fixed *whole* is the error: it justifies burning resources purely to deny rivals while under-investing in the expansion that determines the long-run size of the business.\n\nThe mapped steps:\n1. Contested resource: split into near-term chips/HBM, top talent, and AI productivity — three different units, not one \"race\"\n2. Fixity test: chips fixed (near term), talent fixed (near term), productivity not fixed; all soften over a longer horizon\n3. Bias audit: countability, relative-position, and comparative-advantage blindness all present on the productivity dimension; absent on the fixed-input dimensions\n4. Zero-sum branch: secure fixed compute and talent via supply commitments and retention — minimax capture is correct there\n5. Non-zero-sum branch: expand the productivity pie via platforms, interoperability, and complement strategies — surplus with a named mechanism\n6. Horizon: zero-sum near term on inputs, non-zero-sum longer term and on output — state both, and don't let the first justify neglecting the second\n\n**Diagnosis: Mixed** — genuinely zero-sum on near-term compute and talent, non-zero-sum on the AI-productivity pie. The strategic failure mode of the era is applying a single frame to a mixed game.\n\n*Sources: Von Neumann, J. & Morgenstern, O. (1944), Theory of Games and Economic Behavior, Princeton University Press (definition of zero-sum games and the minimax result); Meegan, D.V. (2010), \"Zero-Sum Bias: Perceived Competition Despite Unlimited Resources,\" Frontiers in Psychology, 1:191 (empirical basis for zero-sum bias). The 2024–2026 characterization of constrained leading-edge AI accelerator and high-bandwidth-memory supply, and of a small frontier-talent pool, reflects widely reported industry conditions during that period; specific allocation figures are omitted deliberately.*\n\nFile v1.0.5:examples/smoot-hawley-tariff-1930.md\n\n# Method in Action: The Smoot-Hawley Tariff and the Fixed-Pie Fallacy in Trade (1930–1934)\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nThe Smoot-Hawley Tariff Act of 1930 is the most consequential documented case of zero-sum misdiagnosis in economic policy — a strategy built on the assumption that trade is a fixed pie, executed at national scale, with measurable results.\n\nThe implicit diagnosis behind the tariff: imports capture American production and jobs, so every unit of imports blocked is a unit of domestic output gained. On this logic, Congress raised duties on over 20,000 imported goods, and President Hoover signed the act in June 1930 — over a petition signed by more than a thousand economists urging a veto. The economists' objection was precisely a zero-sum objection: trade is mutual gain via comparative advantage, and blocking it destroys value on both sides rather than transferring it.\n\nRunning the Diagnosis on the 1930 decision:\n\n**Step 1 (contested resource):** Domestic production and employment in import-competing sectors. Nameable and countable — which is exactly the condition under which zero-sum bias is strongest.\n\n**Step 2 (fixity test):** Fails on all three dimensions. *Cooperation:* trade itself is the cooperative mechanism — specialization by comparative advantage makes total output larger than under autarky, so the \"pie\" of production is not fixed. *Innovation/technology:* export industries expand when trading partners prosper. *Time:* even if a tariff transfers demand to domestic producers this quarter, retaliation and shrinking foreign incomes cut export demand over the following years.\n\n**Step 3 (bias audit):** All three bias markers present. Countability — imports arrive in visible, countable units at ports, while the diffuse gains from trade do not. Relative-position anchoring — the political debate framed foreign producers' sales as America's losses. Comparative-advantage blindness — the analysis treated a dollar of imports as a dollar of forgone domestic production, ignoring that both sides gain from specialization.\n\n**Step 4/5 (what the wrong diagnosis produced):** Because policymakers treated a non-zero-sum game as zero-sum, they played capture instead of designing for surplus. Trading partners ran the same wrong playbook in reverse: Canada — the largest US trading partner — retaliated with duties targeting US exports, and other countries followed with tariffs, quotas, and preferential blocs. Both moves were individually \"rational\" under the fixed-pie frame and collectively destructive outside it. Between 1929 and 1933 world trade collapsed to a fraction of its former volume; the Depression drove much of the fall, but as Irwin documents, the tariff and the retaliation it provoked deepened the contraction and fragmented the world trading system into discriminatory blocs. The pie did not get redivided — it shrank for everyone.\n\n**The corrected diagnosis:** The reversal came only when the game was reframed. The Reciprocal Trade Agreements Act of 1934 abandoned unilateral capture for negotiated mutual tariff reduction — an explicit surplus-capture mechanism (bilateral agreements, later generalized into GATT in 1947). Same players, same \"contested\" trade flows; the strategy flipped from minimax-style protection to cooperative expansion once the non-zero-sum structure was recognized, and postwar trade grew for decades under that frame.\n\n**Stop-rule check:** The non-zero-sum diagnosis here is not wishful cooperation talk — the pie-growth mechanism is concrete (comparative advantage, formalized in reciprocal agreements) and its removal in 1930–1933 produced the predicted mutual loss.\n\nThe mapped steps:\n1. Contested resource: domestic production and jobs in import-competing sectors — countable, hence bias-prone\n2. Fixity test: fails on cooperation (comparative advantage), technology (export growth), and time (retaliation lag) — non-zero-sum\n3. Bias audit: countability, relative-position anchoring, and comparative-advantage blindness all present in the 1930 debate\n4. Wrong-frame consequence: capture strategy triggered retaliatory capture; world trade contracted — mutual loss, not transfer\n5. Corrected strategy: RTAA 1934 → GATT 1947 — a named mechanism converting the game back to cooperative surplus\n\nPrimary source: Irwin, D.A. (2011). *Peddling Protectionism: Smoot-Hawley and the Great Depression.* Princeton University Press.\n\nFile v1.0.5:examples/von-neumann-rand-1944-1950.md\n\n# Method in Action: Von Neumann and the Foundation of Zero-Sum Analysis — RAND, 1944–1950\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nThe zero-sum framework did not originate as a business tool. It was developed to analyze nuclear deterrence.\n\nIn 1944, John von Neumann and Oskar Morgenstern published *Theory of Games and Economic Behavior*, establishing the mathematical foundation of game theory. Their central result for zero-sum games — the Minimax Theorem — had been proved by von Neumann in 1928: in any finite two-person zero-sum game, there exists a mixed-strategy pair such that neither player can improve their expected payoff by unilaterally deviating. The equilibrium payoff to each player is simultaneously the maximum of their minimum guarantee and the minimum of their maximum loss.\n\nBy 1950, RAND Corporation — the primary Cold War strategy think tank — was applying this framework to nuclear deterrence. The core question: is nuclear confrontation between the United States and USSR a zero-sum game? If yes, the minimax solution determines rational deterrence posture. If no — if both parties are worse off under nuclear exchange than under mutual restraint — the situation is a non-zero-sum game requiring a different analysis.\n\nRunning the Diagnosis on Cold War nuclear strategy:\n\n**Step 1 (contested resource):** Global political influence, territorial control, and the absence of nuclear exchange.\n\n**Step 2 (fixity test):** Political influence was partially zero-sum (Soviet gains in Europe meant Western losses). But the *survival of both nations* was non-zero-sum — nuclear exchange destroyed value for both sides simultaneously. Total welfare was not fixed: mutual restraint produced more total survival than mutual escalation.\n\n**Step 3 (bias audit):** Early Cold War strategists committed a countability error — they focused on the zero-sum dimension (territory, influence) and neglected the non-zero-sum dimension (mutual destruction). Schelling's *Strategy of Conflict* (1960) corrected this, showing that the deterrence game was fundamentally non-zero-sum because mutual destruction was the worst outcome for *both* players.\n\n**Step 4/5 (strategy):** Because the game was non-zero-sum, the correct strategy was not minimax but the design of *credible commitment devices* — each side needed to credibly commit to *not* launching a first strike in exchange for reciprocal restraint. Mutual Assured Destruction (MAD) was not a minimax strategy; it was a cooperative equilibrium sustained by credible commitment mechanisms (second-strike capability, hotlines, arms-control treaties).\n\n**Stop-rule applied:** The zero-sum diagnosis was limited to the political dimension. When strategists extended zero-sum reasoning to the nuclear dimension, they produced strategies (first-strike advantages, counterforce targeting) that the non-zero-sum structure showed were collectively irrational. The diagnosis prevented the most dangerous errors.\n\nPrimary sources: Von Neumann, J. & Morgenstern, O. (1944), *Theory of Games and Economic Behavior*, Princeton University Press; Schelling, T.C. (1960), *The Strategy of Conflict*, Harvard University Press.\n\nFile v1.0.5:skill-card.md\n\n## Description:
\nHelps an agent diagnose whether a negotiation, market, policy, or competitive situation is truly zero-sum before choosing capture, minimax, cooperation, or surplus-expansion strategy.
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[deciqai](https://clawhub.ai/user/deciqai)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nEmployees, external users, and strategy-focused agents use this skill to test fixed-pie assumptions in negotiations, markets, policy, trade, and AI competition before choosing a strategic posture. It guides concrete diagnoses by naming contested resources, testing fixity, auditing zero-sum bias, and separating short-term fixed inputs from long-term expandable value.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: The skill can shape strategic, business, policy, or negotiation decisions even though it does not run code or request privileged access.
\nMitigation: Review its framing and recommendations before relying on it for important decisions, especially when stakes are high or evidence about the contested resource is incomplete.
\nRisk: A zero-sum or non-zero-sum diagnosis may be misleading if the contested resource, time horizon, or surplus-capture mechanism is not clearly established.
\nMitigation: Require the skill's verification checks: name the resource, test fixity across technology, cooperation, and time, audit zero-sum bias, and identify a concrete mechanism before acting.
\n\n\n## Reference(s):
\n- [ClawHub Skill Page](https://clawhub.ai/deciqai/skills/zero-sum-game)
\n- [Primary Sources](references/sources.md)
\n- [Von Neumann and Morgenstern, Theory of Games and Economic Behavior](https://press.princeton.edu/books/paperback/9780691130613/theory-of-games-and-economic-behavior)
\n- [Schelling, The Strategy of Conflict](https://www.hup.harvard.edu/books/9780674840317)
\n- [Nash, Equilibrium Points in N-Person Games](https://doi.org/10.1073/pnas.36.1.48)
\n- [Meegan, Zero-Sum Bias](https://doi.org/10.3389/fpsyg.2010.00191)
\n- [International Energy Agency, Energy and AI](https://www.iea.org/reports/energy-and-ai)
\n- [Stanford HAI, AI Index Report 2025](https://hai.stanford.edu/ai-index/2025-ai-index-report)
\n\n\n## Skill Output:
\n**Output Type(s):** [Analysis, Markdown, Guidance]
\n**Output Format:** [Markdown diagnosis and strategic recommendation]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [May ask step-by-step clarification questions in coach mode before producing a diagnosis.]
\n\n## Skill Version(s):
\n1.0.5 (source: ClawHub release evidence)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
\n\nArchive v1.0.4: 6 files, 11415 bytes\n\nFiles: examples/smoot-hawley-tariff-1930.md (4482b), examples/von-neumann-rand-1944-1950.md (3207b), references/sources.md (2420b), skill-card.md (2313b), SKILL.md (9834b), _meta.json (132b)\n\nFile v1.0.4:SKILL.md\n\n---\nname: zero-sum-game\ndescription: \"Activate when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', uses phrases like 'winner-take-all', 'race to the bottom', or 'your gain is my loss', or needs to check whether a negotiation/market/policy situation is truly zero-sum before designing strategy.\n Do NOT activate when: the situation is already confirmed zero-sum (chess, derivatives, fixed-license auctions) and diagnosis is complete — go straight to minimax; or the question is already framed at the equilibrium level — use nash-equilibrium directly.\"\n---\n\n# Zero-Sum Game\n\n## Overview\n\nZero-sum means total value is fixed — one player's gain is another's exact loss. Most real-world competition is NOT zero-sum: the pie can grow, shrink, or be split in many ways. Misdiagnosis sends strategy in the wrong direction from step one. The most consequential error is **zero-sum bias**: the tendency to perceive non-zero-sum situations as zero-sum.\n\nNeighbor skills: use `prisoners-dilemma` when confirmed non-zero-sum but cooperation keeps failing. Use `strategic-commitment` when genuinely zero-sum and you need credible deterrence. Use `nash-equilibrium` for the equilibrium solution in confirmed zero-sum settings.\n\n## When to Use\n\nApply this skill when: entering a competitive situation before determining whether total value is fixed; someone proposes a negotiation assuming \"what I gain, you lose\"; a market entry hinges on whether total market size is fixed; a policy analysis needs to assess whether an intervention redistributes or creates welfare; someone uses zero-sum language (\"winner-take-all\", \"race to the bottom\", \"fixed pie\").\n\n**When NOT to use:** already confirmed zero-sum — go straight to minimax; clear cooperative surplus with no competitive distribution problem; stakes trivial and reversible; question already at equilibrium level — use `nash-equilibrium` directly.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** user has a concrete case → run The Process directly.\n- **Coach mode:** user is unfamiliar or has no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. **One-line what-it-is.** Zero-sum: total value fixed — if I get more, you get less by exactly the same amount. Most real-world competition is NOT zero-sum. The diagnosis changes everything about strategy.\n2. **Check fit.** Is the resource at stake genuinely fixed? If the total can change through cooperation, innovation, or trade, it is likely non-zero-sum.\n3. **Elicit the real case.** Get the specific situation — which market, which negotiation, which policy.\n> **[WAIT — do not advance until user responds]**\n4. **One step at a time.** Walk through the Diagnosis one question per turn. Start with: \"What exactly is being contested — and is the total amount of it fixed?\"\n> **[WAIT — do not advance until user responds]**\n5. **Close by naming the payoff.** State whether zero-sum or not, and what that means for strategy — cooperate/expand vs. minimax/capture.\n> **[WAIT — do not advance until user responds]**\n\n## The Process\n\nRun the **Zero-Sum Diagnosis**. Five gates; confirm or rule out at each one.\n\n1. **Define the contested resource.** State precisely what is being competed over (market share, license, price spread, votes, contract). If you cannot name a concrete unit being divided, the zero-sum frame likely does not apply.\n2. **Test fixity.** Can *innovation/technology* expand the total? Can *cooperation* create additional value? Can *time* change the total? If any answer is \"yes,\" the situation is non-zero-sum in that dimension.\n3. **Check for zero-sum bias.** Are you perceiving zero-sum because the resource is countable? Anchored on relative position over absolute gains? Ignoring comparative advantage? If expansion is feasible, you are in the wrong game.\n4. **If confirmed zero-sum: apply minimax.** Enumerate strategies and worst-case payoffs; choose the strategy maximizing your minimum; consider mixed strategies to prevent exploitation.\n5. **If confirmed non-zero-sum: design for cooperative surplus.** Quantify value neither party gets under pure competition. Specify the mechanism (contract, JV, standard, platform) to capture it. **Stop-rule:** if you cannot identify a concrete pie-growth mechanism, revert to zero-sum analysis.\n6. **State the time horizon.** Many situations are zero-sum short-term and non-zero-sum long-term. State both frames explicitly.\n\n### Output template\n\n```\nZero-Sum Diagnosis: \nContested resource: \nFixity test: innovation | cooperation | time \nBias audit: countability | relative-position | comparative-advantage ignored \nDiagnosis: — confidence \nIf zero-sum → minimax choice: | mixed-strategy consideration: \nIf non-zero-sum → surplus: | mechanism: | structure: \nStrategic recommendation: \n```\n\n*→ Method in Action: [Von Neumann and the Foundation of Zero-Sum Analysis — RAND, 1944–1950](examples/von-neumann-rand-1944-1950.md) · [The Smoot-Hawley Tariff (1930–1934)](examples/smoot-hawley-tariff-1930.md)*\n\n## Game-Type Packs\n\n- **Financial Derivatives:** Zero-sum by contract — every dollar the long gains, the short loses. Minimax applies; cooperation with counterparties is structurally impossible.\n- **Market Share Competition:** Constant-sum short-term; non-zero-sum long-term (category growth, platform effects). Treating long-term markets as zero-sum causes destructive price wars.\n- **Licensing/Spectrum Auctions:** Zero-sum by design — fixed license count. Firms that bid cooperatively lose to rivals who bid to win.\n- **Trade and International Economics:** Non-zero-sum — comparative advantage produces mutual gains. \"Trade deficits = losses\" is an analytical error.\n\n## Applying It Well\n\n- Always state the contested resource precisely before diagnosing — \"competition\" is not a resource.\n- Confirm the time horizon: the same situation can be zero-sum this quarter and non-zero-sum over three years.\n- Non-zero-sum surplus must be *captured*, not just identified — without a credible mechanism it stays theoretical.\n- Zero-sum bias is strongest when resources are countable and socially salient (share rankings, polls). Build in a deliberate check before decisions driven by competitive intel.\n\n*→ Primary sources: [references/sources.md](references/sources.md)*\n\n## Common Rationalizations\n\n**[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.**\n\n| Fake move | Reality |\n|---|---|\n| [D] \"Our market share went down, so we lost\" | Share and value captured differ. If total market grew 50% and share fell 30%→25%, absolute revenue grew. |\n| [D] \"Trade deficits mean we're losing\" | Deficits in goods are offset by export of financial claims. Comparative advantage shows both parties gain. |\n| [D] \"They won the contract, so we lost it\" | One award is zero-sum among bidders. Total industry contracting volume is usually not fixed. |\n| [D] \"We should cooperate — there's value to be created\" | Only correct if non-zero-sum. In genuine zero-sum settings, \"cooperation\" is illegal or a strategic error. |\n| [D] \"It's just market share — zero-sum by definition\" | Market share is a ratio. The denominator is not fixed unless you freeze the time horizon. |\n| [D] \"They made money, so we left money on the table\" | In non-zero-sum negotiation both parties can gain. Counterparty's gain implies your loss only if truly zero-sum. |\n| [D] \"Race to the bottom on price — classic zero-sum\" | Zero-sum on margin within a fixed pool, but non-zero-sum if lower prices expand total demand. |\n| [D] \"My industry experience says it's zero-sum\" | Intuitions fail at inflection points. Run diagnosis from first principles on the current structure. |\n| *→ Add [O] entries here after each real use — paste the actual failure pattern* | *What went wrong and why* |\n\n## Red Flags\n\n- Contested resource never explicitly named or tested for fixity\n- \"Zero-sum\" concluded because competition *feels* intense, not from resource structure\n- Non-zero-sum used to justify cooperation without identifying a concrete surplus-capture mechanism\n- Time horizon not specified — \"zero-sum\" treated as time-invariant\n- Zero-sum bias not audited (countability, relative position, comparative advantage)\n- Minimax applied to a non-zero-sum situation; or cooperation proposed in a genuinely zero-sum situation\n\n## Verification\n\n- [ ] Contested resource named precisely with the specific unit being divided\n- [ ] Fixity test run on all three dimensions: technology, cooperation, time horizon\n- [ ] Zero-sum bias audited: countability, relative-position anchoring, comparative-advantage blindness\n- [ ] Diagnosis states game type with reasoning; time horizon specified for both short and long term\n- [ ] If zero-sum: minimax strategy identified including mixed-strategy consideration\n- [ ] If non-zero-sum: surplus estimated, mechanism named, structural capture mechanism proposed\n- [ ] Stop-rule applied: non-zero-sum confirmed by identifiable mechanism, not assumed from desire to cooperate\n\n---\n\n*Part of **deciqAI Knowledge Skills** — 164 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. **See it run → https://www.deciqai.com/c/zero-sum-game** · ⭐ Star the repo → https://github.com/deciqAI/knowledge-skills · Contributions welcome.*\n\nFile v1.0.4:_meta.json\n\n{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"zero-sum-game\",\n \"version\": \"1.0.4\",\n \"publishedAt\": 1783509916810\n}\n\nFile v1.0.4:references/sources.md\n\n# Sources — zero-sum-game\n\n> *Primary sources for the [zero-sum-game](../SKILL.md) skill.*\n\n- Von Neumann, J. & Morgenstern, O. (1944). *Theory of Games and Economic Behavior.* Princeton University Press. The founding text of game theory; contains the Minimax Theorem and the formal definition of zero-sum games. Reprint available via Princeton University Press. https://press.princeton.edu/books/paperback/9780691130613/theory-of-games-and-economic-behavior\n- Schelling, T.C. (1960). *The Strategy of Conflict.* Harvard University Press. The canonical analysis of zero-sum vs. non-zero-sum conflict in negotiation and deterrence, including the Cold War application. https://www.hup.harvard.edu/books/9780674840317\n- Nash, J. F. (1950). \"Equilibrium Points in n-Person Games.\" *Proceedings of the National Academy of Sciences*, 36(1), pp. 48–49. The equilibrium concept that generalizes beyond zero-sum settings; for zero-sum games, Nash equilibrium coincides with minimax. https://doi.org/10.1073/pnas.36.1.48\n- Meegan, D.V. (2010). \"Zero-Sum Bias: Perceived Competition Despite Unlimited Resources.\" *Frontiers in Psychology*, 1, 191. Primary empirical documentation of zero-sum bias as a cognitive phenomenon — the systematic tendency to perceive zero-sum structures when they are not present. https://doi.org/10.3389/fpsyg.2010.00191\n- Dixit, A. & Nalebuff, B. (1991). *Thinking Strategically.* W.W. Norton. The standard practical treatment of zero-sum vs. non-zero-sum games for practitioners; Chapter 4 covers the distinction in business contexts. ISBN 978-0393310351.\n- Irwin, D.A. (2011). *Peddling Protectionism: Smoot-Hawley and the Great Depression.* Princeton University Press. The definitive historical account of the 1930 tariff — the political economy of its passage, the foreign retaliation it provoked, and its role in the collapse and fragmentation of world trade; the canonical documented case of zero-sum misdiagnosis in trade policy. ISBN 978-0691150321.\n\n**What is not cited and why:** Popular business writing frequently attributes the phrase \"zero-sum game\" to competitive strategy without checking whether the specific situation meets the mathematical definition. Claims that \"competition is always zero-sum\" or \"negotiation is always zero-sum\" are asserted but unverified. This skill uses the mathematical definition from Von Neumann and Morgenstern as the anchor, not intuitive usage.\n\nFile v1.0.4:examples/smoot-hawley-tariff-1930.md\n\n# Method in Action: The Smoot-Hawley Tariff and the Fixed-Pie Fallacy in Trade (1930–1934)\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nThe Smoot-Hawley Tariff Act of 1930 is the most consequential documented case of zero-sum misdiagnosis in economic policy — a strategy built on the assumption that trade is a fixed pie, executed at national scale, with measurable results.\n\nThe implicit diagnosis behind the tariff: imports capture American production and jobs, so every unit of imports blocked is a unit of domestic output gained. On this logic, Congress raised duties on over 20,000 imported goods, and President Hoover signed the act in June 1930 — over a petition signed by more than a thousand economists urging a veto. The economists' objection was precisely a zero-sum objection: trade is mutual gain via comparative advantage, and blocking it destroys value on both sides rather than transferring it.\n\nRunning the Diagnosis on the 1930 decision:\n\n**Step 1 (contested resource):** Domestic production and employment in import-competing sectors. Nameable and countable — which is exactly the condition under which zero-sum bias is strongest.\n\n**Step 2 (fixity test):** Fails on all three dimensions. *Cooperation:* trade itself is the cooperative mechanism — specialization by comparative advantage makes total output larger than under autarky, so the \"pie\" of production is not fixed. *Innovation/technology:* export industries expand when trading partners prosper. *Time:* even if a tariff transfers demand to domestic producers this quarter, retaliation and shrinking foreign incomes cut export demand over the following years.\n\n**Step 3 (bias audit):** All three bias markers present. Countability — imports arrive in visible, countable units at ports, while the diffuse gains from trade do not. Relative-position anchoring — the political debate framed foreign producers' sales as America's losses. Comparative-advantage blindness — the analysis treated a dollar of imports as a dollar of forgone domestic production, ignoring that both sides gain from specialization.\n\n**Step 4/5 (what the wrong diagnosis produced):** Because policymakers treated a non-zero-sum game as zero-sum, they played capture instead of designing for surplus. Trading partners ran the same wrong playbook in reverse: Canada — the largest US trading partner — retaliated with duties targeting US exports, and other countries followed with tariffs, quotas, and preferential blocs. Both moves were individually \"rational\" under the fixed-pie frame and collectively destructive outside it. Between 1929 and 1933 world trade collapsed to a fraction of its former volume; the Depression drove much of the fall, but as Irwin documents, the tariff and the retaliation it provoked deepened the contraction and fragmented the world trading system into discriminatory blocs. The pie did not get redivided — it shrank for everyone.\n\n**The corrected diagnosis:** The reversal came only when the game was reframed. The Reciprocal Trade Agreements Act of 1934 abandoned unilateral capture for negotiated mutual tariff reduction — an explicit surplus-capture mechanism (bilateral agreements, later generalized into GATT in 1947). Same players, same \"contested\" trade flows; the strategy flipped from minimax-style protection to cooperative expansion once the non-zero-sum structure was recognized, and postwar trade grew for decades under that frame.\n\n**Stop-rule check:** The non-zero-sum diagnosis here is not wishful cooperation talk — the pie-growth mechanism is concrete (comparative advantage, formalized in reciprocal agreements) and its removal in 1930–1933 produced the predicted mutual loss.\n\nThe mapped steps:\n1. Contested resource: domestic production and jobs in import-competing sectors — countable, hence bias-prone\n2. Fixity test: fails on cooperation (comparative advantage), technology (export growth), and time (retaliation lag) — non-zero-sum\n3. Bias audit: countability, relative-position anchoring, and comparative-advantage blindness all present in the 1930 debate\n4. Wrong-frame consequence: capture strategy triggered retaliatory capture; world trade contracted — mutual loss, not transfer\n5. Corrected strategy: RTAA 1934 → GATT 1947 — a named mechanism converting the game back to cooperative surplus\n\nPrimary source: Irwin, D.A. (2011). *Peddling Protectionism: Smoot-Hawley and the Great Depression.* Princeton University Press.\n\nFile v1.0.4:examples/von-neumann-rand-1944-1950.md\n\n# Method in Action: Von Neumann and the Foundation of Zero-Sum Analysis — RAND, 1944–1950\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nThe zero-sum framework did not originate as a business tool. It was developed to analyze nuclear deterrence.\n\nIn 1944, John von Neumann and Oskar Morgenstern published *Theory of Games and Economic Behavior*, establishing the mathematical foundation of game theory. Their central result for zero-sum games — the Minimax Theorem — had been proved by von Neumann in 1928: in any finite two-person zero-sum game, there exists a mixed-strategy pair such that neither player can improve their expected payoff by unilaterally deviating. The equilibrium payoff to each player is simultaneously the maximum of their minimum guarantee and the minimum of their maximum loss.\n\nBy 1950, RAND Corporation — the primary Cold War strategy think tank — was applying this framework to nuclear deterrence. The core question: is nuclear confrontation between the United States and USSR a zero-sum game? If yes, the minimax solution determines rational deterrence posture. If no — if both parties are worse off under nuclear exchange than under mutual restraint — the situation is a non-zero-sum game requiring a different analysis.\n\nRunning the Diagnosis on Cold War nuclear strategy:\n\n**Step 1 (contested resource):** Global political influence, territorial control, and the absence of nuclear exchange.\n\n**Step 2 (fixity test):** Political influence was partially zero-sum (Soviet gains in Europe meant Western losses). But the *survival of both nations* was non-zero-sum — nuclear exchange destroyed value for both sides simultaneously. Total welfare was not fixed: mutual restraint produced more total survival than mutual escalation.\n\n**Step 3 (bias audit):** Early Cold War strategists committed a countability error — they focused on the zero-sum dimension (territory, influence) and neglected the non-zero-sum dimension (mutual destruction). Schelling's *Strategy of Conflict* (1960) corrected this, showing that the deterrence game was fundamentally non-zero-sum because mutual destruction was the worst outcome for *both* players.\n\n**Step 4/5 (strategy):** Because the game was non-zero-sum, the correct strategy was not minimax but the design of *credible commitment devices* — each side needed to credibly commit to *not* launching a first strike in exchange for reciprocal restraint. Mutual Assured Destruction (MAD) was not a minimax strategy; it was a cooperative equilibrium sustained by credible commitment mechanisms (second-strike capability, hotlines, arms-control treaties).\n\n**Stop-rule applied:** The zero-sum diagnosis was limited to the political dimension. When strategists extended zero-sum reasoning to the nuclear dimension, they produced strategies (first-strike advantages, counterforce targeting) that the non-zero-sum structure showed were collectively irrational. The diagnosis prevented the most dangerous errors.\n\nPrimary sources: Von Neumann, J. & Morgenstern, O. (1944), *Theory of Games and Economic Behavior*, Princeton University Press; Schelling, T.C. (1960), *The Strategy of Conflict*, Harvard University Press.\n\nFile v1.0.4:skill-card.md\n\n## Description:
\nHelps agents diagnose whether negotiations, markets, policy choices, or competitive situations are truly zero-sum before choosing cooperation, minimax, or surplus-creation strategy.
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[deciqai](https://clawhub.ai/user/deciqai)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nBusiness strategists, policy analysts, and agents use this skill to test whether value is fixed or expandable before recommending competitive, cooperative, or minimax strategy.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: The skill can influence strategic business or policy advice if its diagnosis is treated as decisive.
\nMitigation: Use it as reasoning support and apply human judgment for high-stakes decisions.
\n\n\n## Reference(s):
\n- [Sources - zero-sum-game](references/sources.md)
\n- [Von Neumann and the Foundation of Zero-Sum Analysis - RAND, 1944-1950](examples/von-neumann-rand-1944-1950.md)
\n- [The Smoot-Hawley Tariff and the Fixed-Pie Fallacy in Trade, 1930-1934](examples/smoot-hawley-tariff-1930.md)
\n- [Theory of Games and Economic Behavior](https://press.princeton.edu/books/paperback/9780691130613/theory-of-games-and-economic-behavior)
\n- [The Strategy of Conflict](https://www.hup.harvard.edu/books/9780674840317)
\n- [Equilibrium Points in N-Person Games](https://doi.org/10.1073/pnas.36.1.48)
\n- [Zero-Sum Bias: Perceived Competition Despite Unlimited Resources](https://doi.org/10.3389/fpsyg.2010.00191)
\n\n\n## Skill Output:
\n**Output Type(s):** [text, markdown, guidance]
\n**Output Format:** [Markdown diagnostic analysis with structured fields and recommendations]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [Interactive coaching mode may ask one question at a time before producing a diagnosis.]
\n\n## Skill Version(s):
\n1.0.4 (source: server release evidence)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
\n\nArchive v1.0.3: 6 files, 11215 bytes\n\nFiles: examples/smoot-hawley-tariff-1930.md (4482b), examples/von-neumann-rand-1944-1950.md (3207b), references/sources.md (2420b), skill-card.md (1921b), SKILL.md (9937b), _meta.json (132b)\n\nFile v1.0.3:SKILL.md\n\n---\nname: zero-sum-game\ndescription: \"Activate when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', uses phrases like 'winner-take-all', 'race to the bottom', or 'your gain is my loss', or needs to check whether a negotiation/market/policy situation is truly zero-sum before designing strategy.\n Do NOT activate when: the situation is already confirmed zero-sum (chess, derivatives, fixed-license auctions) and diagnosis is complete — go straight to minimax; or the question is already framed at the equilibrium level — use nash-equilibrium directly.\"\n---\n\n# Zero-Sum Game\n\n## Overview\n\nZero-sum means total value is fixed — one player's gain is another's exact loss. Most real-world competition is NOT zero-sum: the pie can grow, shrink, or be split in many ways. Misdiagnosis sends strategy in the wrong direction from step one. The most consequential error is **zero-sum bias**: the tendency to perceive non-zero-sum situations as zero-sum.\n\nNeighbor skills: use `prisoners-dilemma` when confirmed non-zero-sum but cooperation keeps failing. Use `strategic-commitment` when genuinely zero-sum and you need credible deterrence. Use `nash-equilibrium` for the equilibrium solution in confirmed zero-sum settings.\n\n## When to Use\n\nApply this skill when: entering a competitive situation before determining whether total value is fixed; someone proposes a negotiation assuming \"what I gain, you lose\"; a market entry hinges on whether total market size is fixed; a policy analysis needs to assess whether an intervention redistributes or creates welfare; someone uses zero-sum language (\"winner-take-all\", \"race to the bottom\", \"fixed pie\").\n\n**When NOT to use:** already confirmed zero-sum — go straight to minimax; clear cooperative surplus with no competitive distribution problem; stakes trivial and reversible; question already at equilibrium level — use `nash-equilibrium` directly.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** user has a concrete case → run The Process directly.\n- **Coach mode:** user is unfamiliar or has no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. **One-line what-it-is.** Zero-sum: total value fixed — if I get more, you get less by exactly the same amount. Most real-world competition is NOT zero-sum. The diagnosis changes everything about strategy.\n2. **Check fit.** Is the resource at stake genuinely fixed? If the total can change through cooperation, innovation, or trade, it is likely non-zero-sum.\n3. **Elicit the real case.** Get the specific situation — which market, which negotiation, which policy.\n> **[WAIT — do not advance until user responds]**\n4. **One step at a time.** Walk through the Diagnosis one question per turn. Start with: \"What exactly is being contested — and is the total amount of it fixed?\"\n> **[WAIT — do not advance until user responds]**\n5. **Close by naming the payoff.** State whether zero-sum or not, and what that means for strategy — cooperate/expand vs. minimax/capture.\n> **[WAIT — do not advance until user responds]**\n\n## The Process\n\nRun the **Zero-Sum Diagnosis**. Five gates; confirm or rule out at each one.\n\n1. **Define the contested resource.** State precisely what is being competed over (market share, license, price spread, votes, contract). If you cannot name a concrete unit being divided, the zero-sum frame likely does not apply.\n2. **Test fixity.** Can *innovation/technology* expand the total? Can *cooperation* create additional value? Can *time* change the total? If any answer is \"yes,\" the situation is non-zero-sum in that dimension.\n3. **Check for zero-sum bias.** Are you perceiving zero-sum because the resource is countable? Anchored on relative position over absolute gains? Ignoring comparative advantage? If expansion is feasible, you are in the wrong game.\n4. **If confirmed zero-sum: apply minimax.** Enumerate strategies and worst-case payoffs; choose the strategy maximizing your minimum; consider mixed strategies to prevent exploitation.\n5. **If confirmed non-zero-sum: design for cooperative surplus.** Quantify value neither party gets under pure competition. Specify the mechanism (contract, JV, standard, platform) to capture it. **Stop-rule:** if you cannot identify a concrete pie-growth mechanism, revert to zero-sum analysis.\n6. **State the time horizon.** Many situations are zero-sum short-term and non-zero-sum long-term. State both frames explicitly.\n\n### Output template\n\n```\nZero-Sum Diagnosis: \nContested resource: \nFixity test: innovation | cooperation | time \nBias audit: countability | relative-position | comparative-advantage ignored \nDiagnosis: — confidence \nIf zero-sum → minimax choice: | mixed-strategy consideration: \nIf non-zero-sum → surplus: | mechanism: | structure: \nStrategic recommendation: \n```\n\n*→ Method in Action: [Von Neumann and the Foundation of Zero-Sum Analysis — RAND, 1944–1950](examples/von-neumann-rand-1944-1950.md) · [The Smoot-Hawley Tariff (1930–1934)](examples/smoot-hawley-tariff-1930.md)*\n\n## Game-Type Packs\n\n- **Financial Derivatives:** Zero-sum by contract — every dollar the long gains, the short loses. Minimax applies; cooperation with counterparties is structurally impossible.\n- **Market Share Competition:** Constant-sum short-term; non-zero-sum long-term (category growth, platform effects). Treating long-term markets as zero-sum causes destructive price wars.\n- **Licensing/Spectrum Auctions:** Zero-sum by design — fixed license count. Firms that bid cooperatively lose to rivals who bid to win.\n- **Trade and International Economics:** Non-zero-sum — comparative advantage produces mutual gains. \"Trade deficits = losses\" is an analytical error.\n\n## Applying It Well\n\n- Always state the contested resource precisely before diagnosing — \"competition\" is not a resource.\n- Confirm the time horizon: the same situation can be zero-sum this quarter and non-zero-sum over three years.\n- Non-zero-sum surplus must be *captured*, not just identified — without a credible mechanism it stays theoretical.\n- Zero-sum bias is strongest when resources are countable and socially salient (share rankings, polls). Build in a deliberate check before decisions driven by competitive intel.\n\n*→ Primary sources: [references/sources.md](references/sources.md)*\n\n## Common Rationalizations\n\n**[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.**\n\n| Fake move | Reality |\n|---|---|\n| [D] \"Our market share went down, so we lost\" | Share and value captured differ. If total market grew 50% and share fell 30%→25%, absolute revenue grew. |\n| [D] \"Trade deficits mean we're losing\" | Deficits in goods are offset by export of financial claims. Comparative advantage shows both parties gain. |\n| [D] \"They won the contract, so we lost it\" | One award is zero-sum among bidders. Total industry contracting volume is usually not fixed. |\n| [D] \"We should cooperate — there's value to be created\" | Only correct if non-zero-sum. In genuine zero-sum settings, \"cooperation\" is illegal or a strategic error. |\n| [D] \"It's just market share — zero-sum by definition\" | Market share is a ratio. The denominator is not fixed unless you freeze the time horizon. |\n| [D] \"They made money, so we left money on the table\" | In non-zero-sum negotiation both parties can gain. Counterparty's gain implies your loss only if truly zero-sum. |\n| [D] \"Race to the bottom on price — classic zero-sum\" | Zero-sum on margin within a fixed pool, but non-zero-sum if lower prices expand total demand. |\n| [D] \"My industry experience says it's zero-sum\" | Intuitions fail at inflection points. Run diagnosis from first principles on the current structure. |\n| *→ Add [O] entries here after each real use — paste the actual failure pattern* | *What went wrong and why* |\n\n## Red Flags\n\n- Contested resource never explicitly named or tested for fixity\n- \"Zero-sum\" concluded because competition *feels* intense, not from resource structure\n- Non-zero-sum used to justify cooperation without identifying a concrete surplus-capture mechanism\n- Time horizon not specified — \"zero-sum\" treated as time-invariant\n- Zero-sum bias not audited (countability, relative position, comparative advantage)\n- Minimax applied to a non-zero-sum situation; or cooperation proposed in a genuinely zero-sum situation\n\n## Verification\n\n- [ ] Contested resource named precisely with the specific unit being divided\n- [ ] Fixity test run on all three dimensions: technology, cooperation, time horizon\n- [ ] Zero-sum bias audited: countability, relative-position anchoring, comparative-advantage blindness\n- [ ] Diagnosis states game type with reasoning; time horizon specified for both short and long term\n- [ ] If zero-sum: minimax strategy identified including mixed-strategy consideration\n- [ ] If non-zero-sum: surplus estimated, mechanism named, structural capture mechanism proposed\n- [ ] Stop-rule applied: non-zero-sum confirmed by identifiable mechanism, not assumed from desire to cooperate\n\n---\n\n*Part of **deciqAI Knowledge Skills** — 163 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. **See it run → https://www.deciqai.com/skills/zero-sum-game?utm_source=clawhub&utm_medium=marketplace&utm_campaign=knowledge-skills&utm_content=zero-sum-game** · ⭐ Star the repo → https://github.com/deciqAI/knowledge-skills · Contributions welcome.*\n\nFile v1.0.3:_meta.json\n\n{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"zero-sum-game\",\n \"version\": \"1.0.3\",\n \"publishedAt\": 1783482802373\n}\n\nFile v1.0.3:references/sources.md\n\n# Sources — zero-sum-game\n\n> *Primary sources for the [zero-sum-game](../SKILL.md) skill.*\n\n- Von Neumann, J. & Morgenstern, O. (1944). *Theory of Games and Economic Behavior.* Princeton University Press. The founding text of game theory; contains the Minimax Theorem and the formal definition of zero-sum games. Reprint available via Princeton University Press. https://press.princeton.edu/books/paperback/9780691130613/theory-of-games-and-economic-behavior\n- Schelling, T.C. (1960). *The Strategy of Conflict.* Harvard University Press. The canonical analysis of zero-sum vs. non-zero-sum conflict in negotiation and deterrence, including the Cold War application. https://www.hup.harvard.edu/books/9780674840317\n- Nash, J. F. (1950). \"Equilibrium Points in n-Person Games.\" *Proceedings of the National Academy of Sciences*, 36(1), pp. 48–49. The equilibrium concept that generalizes beyond zero-sum settings; for zero-sum games, Nash equilibrium coincides with minimax. https://doi.org/10.1073/pnas.36.1.48\n- Meegan, D.V. (2010). \"Zero-Sum Bias: Perceived Competition Despite Unlimited Resources.\" *Frontiers in Psychology*, 1, 191. Primary empirical documentation of zero-sum bias as a cognitive phenomenon — the systematic tendency to perceive zero-sum structures when they are not present. https://doi.org/10.3389/fpsyg.2010.00191\n- Dixit, A. & Nalebuff, B. (1991). *Thinking Strategically.* W.W. Norton. The standard practical treatment of zero-sum vs. non-zero-sum games for practitioners; Chapter 4 covers the distinction in business contexts. ISBN 978-0393310351.\n- Irwin, D.A. (2011). *Peddling Protectionism: Smoot-Hawley and the Great Depression.* Princeton University Press. The definitive historical account of the 1930 tariff — the political economy of its passage, the foreign retaliation it provoked, and its role in the collapse and fragmentation of world trade; the canonical documented case of zero-sum misdiagnosis in trade policy. ISBN 978-0691150321.\n\n**What is not cited and why:** Popular business writing frequently attributes the phrase \"zero-sum game\" to competitive strategy without checking whether the specific situation meets the mathematical definition. Claims that \"competition is always zero-sum\" or \"negotiation is always zero-sum\" are asserted but unverified. This skill uses the mathematical definition from Von Neumann and Morgenstern as the anchor, not intuitive usage.\n\nFile v1.0.3:examples/smoot-hawley-tariff-1930.md\n\n# Method in Action: The Smoot-Hawley Tariff and the Fixed-Pie Fallacy in Trade (1930–1934)\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nThe Smoot-Hawley Tariff Act of 1930 is the most consequential documented case of zero-sum misdiagnosis in economic policy — a strategy built on the assumption that trade is a fixed pie, executed at national scale, with measurable results.\n\nThe implicit diagnosis behind the tariff: imports capture American production and jobs, so every unit of imports blocked is a unit of domestic output gained. On this logic, Congress raised duties on over 20,000 imported goods, and President Hoover signed the act in June 1930 — over a petition signed by more than a thousand economists urging a veto. The economists' objection was precisely a zero-sum objection: trade is mutual gain via comparative advantage, and blocking it destroys value on both sides rather than transferring it.\n\nRunning the Diagnosis on the 1930 decision:\n\n**Step 1 (contested resource):** Domestic production and employment in import-competing sectors. Nameable and countable — which is exactly the condition under which zero-sum bias is strongest.\n\n**Step 2 (fixity test):** Fails on all three dimensions. *Cooperation:* trade itself is the cooperative mechanism — specialization by comparative advantage makes total output larger than under autarky, so the \"pie\" of production is not fixed. *Innovation/technology:* export industries expand when trading partners prosper. *Time:* even if a tariff transfers demand to domestic producers this quarter, retaliation and shrinking foreign incomes cut export demand over the following years.\n\n**Step 3 (bias audit):** All three bias markers present. Countability — imports arrive in visible, countable units at ports, while the diffuse gains from trade do not. Relative-position anchoring — the political debate framed foreign producers' sales as America's losses. Comparative-advantage blindness — the analysis treated a dollar of imports as a dollar of forgone domestic production, ignoring that both sides gain from specialization.\n\n**Step 4/5 (what the wrong diagnosis produced):** Because policymakers treated a non-zero-sum game as zero-sum, they played capture instead of designing for surplus. Trading partners ran the same wrong playbook in reverse: Canada — the largest US trading partner — retaliated with duties targeting US exports, and other countries followed with tariffs, quotas, and preferential blocs. Both moves were individually \"rational\" under the fixed-pie frame and collectively destructive outside it. Between 1929 and 1933 world trade collapsed to a fraction of its former volume; the Depression drove much of the fall, but as Irwin documents, the tariff and the retaliation it provoked deepened the contraction and fragmented the world trading system into discriminatory blocs. The pie did not get redivided — it shrank for everyone.\n\n**The corrected diagnosis:** The reversal came only when the game was reframed. The Reciprocal Trade Agreements Act of 1934 abandoned unilateral capture for negotiated mutual tariff reduction — an explicit surplus-capture mechanism (bilateral agreements, later generalized into GATT in 1947). Same players, same \"contested\" trade flows; the strategy flipped from minimax-style protection to cooperative expansion once the non-zero-sum structure was recognized, and postwar trade grew for decades under that frame.\n\n**Stop-rule check:** The non-zero-sum diagnosis here is not wishful cooperation talk — the pie-growth mechanism is concrete (comparative advantage, formalized in reciprocal agreements) and its removal in 1930–1933 produced the predicted mutual loss.\n\nThe mapped steps:\n1. Contested resource: domestic production and jobs in import-competing sectors — countable, hence bias-prone\n2. Fixity test: fails on cooperation (comparative advantage), technology (export growth), and time (retaliation lag) — non-zero-sum\n3. Bias audit: countability, relative-position anchoring, and comparative-advantage blindness all present in the 1930 debate\n4. Wrong-frame consequence: capture strategy triggered retaliatory capture; world trade contracted — mutual loss, not transfer\n5. Corrected strategy: RTAA 1934 → GATT 1947 — a named mechanism converting the game back to cooperative surplus\n\nPrimary source: Irwin, D.A. (2011). *Peddling Protectionism: Smoot-Hawley and the Great Depression.* Princeton University Press.\n\nFile v1.0.3:examples/von-neumann-rand-1944-1950.md\n\n# Method in Action: Von Neumann and the Foundation of Zero-Sum Analysis — RAND, 1944–1950\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nThe zero-sum framework did not originate as a business tool. It was developed to analyze nuclear deterrence.\n\nIn 1944, John von Neumann and Oskar Morgenstern published *Theory of Games and Economic Behavior*, establishing the mathematical foundation of game theory. Their central result for zero-sum games — the Minimax Theorem — had been proved by von Neumann in 1928: in any finite two-person zero-sum game, there exists a mixed-strategy pair such that neither player can improve their expected payoff by unilaterally deviating. The equilibrium payoff to each player is simultaneously the maximum of their minimum guarantee and the minimum of their maximum loss.\n\nBy 1950, RAND Corporation — the primary Cold War strategy think tank — was applying this framework to nuclear deterrence. The core question: is nuclear confrontation between the United States and USSR a zero-sum game? If yes, the minimax solution determines rational deterrence posture. If no — if both parties are worse off under nuclear exchange than under mutual restraint — the situation is a non-zero-sum game requiring a different analysis.\n\nRunning the Diagnosis on Cold War nuclear strategy:\n\n**Step 1 (contested resource):** Global political influence, territorial control, and the absence of nuclear exchange.\n\n**Step 2 (fixity test):** Political influence was partially zero-sum (Soviet gains in Europe meant Western losses). But the *survival of both nations* was non-zero-sum — nuclear exchange destroyed value for both sides simultaneously. Total welfare was not fixed: mutual restraint produced more total survival than mutual escalation.\n\n**Step 3 (bias audit):** Early Cold War strategists committed a countability error — they focused on the zero-sum dimension (territory, influence) and neglected the non-zero-sum dimension (mutual destruction). Schelling's *Strategy of Conflict* (1960) corrected this, showing that the deterrence game was fundamentally non-zero-sum because mutual destruction was the worst outcome for *both* players.\n\n**Step 4/5 (strategy):** Because the game was non-zero-sum, the correct strategy was not minimax but the design of *credible commitment devices* — each side needed to credibly commit to *not* launching a first strike in exchange for reciprocal restraint. Mutual Assured Destruction (MAD) was not a minimax strategy; it was a cooperative equilibrium sustained by credible commitment mechanisms (second-strike capability, hotlines, arms-control treaties).\n\n**Stop-rule applied:** The zero-sum diagnosis was limited to the political dimension. When strategists extended zero-sum reasoning to the nuclear dimension, they produced strategies (first-strike advantages, counterforce targeting) that the non-zero-sum structure showed were collectively irrational. The diagnosis prevented the most dangerous errors.\n\nPrimary sources: Von Neumann, J. & Morgenstern, O. (1944), *Theory of Games and Economic Behavior*, Princeton University Press; Schelling, T.C. (1960), *The Strategy of Conflict*, Harvard University Press.\n\nFile v1.0.3:skill-card.md\n\n## Description:
\nHelps an agent diagnose whether a market, negotiation, policy, or competitive situation is truly zero-sum before recommending cooperation, minimax, or surplus-creation strategy.
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[deciqai](https://clawhub.ai/user/deciqai)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nDevelopers and agent builders use this skill to help agents evaluate fixed-pie assumptions, audit zero-sum bias, and produce structured strategic recommendations for business, negotiation, policy, and game-theory scenarios.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: Business or policy recommendations may be mistaken for authoritative decisions.
\nMitigation: Treat outputs as strategy analysis and require human review before taking real-world action.
\n\n\n## Reference(s):
\n- [ClawHub skill page](https://clawhub.ai/deciqai/skills/zero-sum-game)
\n- [Primary sources](references/sources.md)
\n- [Von Neumann and RAND example](examples/von-neumann-rand-1944-1950.md)
\n- [Smoot-Hawley Tariff example](examples/smoot-hawley-tariff-1930.md)
\n\n\n## Skill Output:
\n**Output Type(s):** [text, markdown, guidance]
\n**Output Format:** [Markdown diagnosis template with concise strategic recommendation text]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [Produces structured zero-sum diagnosis fields, bias audit results, confidence, and strategy guidance.]
\n\n## Skill Version(s):
\n1.0.3 (source: server release metadata)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
\n\nArchive v1.0.2: 5 files, 8978 bytes\n\nFiles: examples/von-neumann-rand-1944-1950.md (3207b), references/sources.md (2017b), skill-card.md (2505b), SKILL.md (9856b), _meta.json (132b)\n\nFile v1.0.2:SKILL.md\n\n---\nname: zero-sum-game\ndescription: \"Activate when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', uses phrases like 'winner-take-all', 'race to the bottom', or 'your gain is my loss', or needs to check whether a negotiation/market/policy situation is truly zero-sum before designing strategy.\n Do NOT activate when: the situation is already confirmed zero-sum (chess, derivatives, fixed-license auctions) and diagnosis is complete — go straight to minimax; or the question is already framed at the equilibrium level — use nash-equilibrium directly.\"\n---\n\n# Zero-Sum Game\n\n## Overview\n\nZero-sum means total value is fixed — one player's gain is another's exact loss. Most real-world competition is NOT zero-sum: the pie can grow, shrink, or be split in many ways. Misdiagnosis sends strategy in the wrong direction from step one. The most consequential error is **zero-sum bias**: the tendency to perceive non-zero-sum situations as zero-sum.\n\nNeighbor skills: use `prisoners-dilemma` when confirmed non-zero-sum but cooperation keeps failing. Use `strategic-commitment` when genuinely zero-sum and you need credible deterrence. Use `nash-equilibrium` for the equilibrium solution in confirmed zero-sum settings.\n\n## When to Use\n\nApply this skill when: entering a competitive situation before determining whether total value is fixed; someone proposes a negotiation assuming \"what I gain, you lose\"; a market entry hinges on whether total market size is fixed; a policy analysis needs to assess whether an intervention redistributes or creates welfare; someone uses zero-sum language (\"winner-take-all\", \"race to the bottom\", \"fixed pie\").\n\n**When NOT to use:** already confirmed zero-sum — go straight to minimax; clear cooperative surplus with no competitive distribution problem; stakes trivial and reversible; question already at equilibrium level — use `nash-equilibrium` directly.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** user has a concrete case → run The Process directly.\n- **Coach mode:** user is unfamiliar or has no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. **One-line what-it-is.** Zero-sum: total value fixed — if I get more, you get less by exactly the same amount. Most real-world competition is NOT zero-sum. The diagnosis changes everything about strategy.\n2. **Check fit.** Is the resource at stake genuinely fixed? If the total can change through cooperation, innovation, or trade, it is likely non-zero-sum.\n3. **Elicit the real case.** Get the specific situation — which market, which negotiation, which policy.\n> **[WAIT — do not advance until user responds]**\n4. **One step at a time.** Walk through the Diagnosis one question per turn. Start with: \"What exactly is being contested — and is the total amount of it fixed?\"\n> **[WAIT — do not advance until user responds]**\n5. **Close by naming the payoff.** State whether zero-sum or not, and what that means for strategy — cooperate/expand vs. minimax/capture.\n> **[WAIT — do not advance until user responds]**\n\n## The Process\n\nRun the **Zero-Sum Diagnosis**. Five gates; confirm or rule out at each one.\n\n1. **Define the contested resource.** State precisely what is being competed over (market share, license, price spread, votes, contract). If you cannot name a concrete unit being divided, the zero-sum frame likely does not apply.\n2. **Test fixity.** Can *innovation/technology* expand the total? Can *cooperation* create additional value? Can *time* change the total? If any answer is \"yes,\" the situation is non-zero-sum in that dimension.\n3. **Check for zero-sum bias.** Are you perceiving zero-sum because the resource is countable? Anchored on relative position over absolute gains? Ignoring comparative advantage? If expansion is feasible, you are in the wrong game.\n4. **If confirmed zero-sum: apply minimax.** Enumerate strategies and worst-case payoffs; choose the strategy maximizing your minimum; consider mixed strategies to prevent exploitation.\n5. **If confirmed non-zero-sum: design for cooperative surplus.** Quantify value neither party gets under pure competition. Specify the mechanism (contract, JV, standard, platform) to capture it. **Stop-rule:** if you cannot identify a concrete pie-growth mechanism, revert to zero-sum analysis.\n6. **State the time horizon.** Many situations are zero-sum short-term and non-zero-sum long-term. State both frames explicitly.\n\n### Output template\n\n```\nZero-Sum Diagnosis: \nContested resource: \nFixity test: innovation | cooperation | time \nBias audit: countability | relative-position | comparative-advantage ignored \nDiagnosis: — confidence \nIf zero-sum → minimax choice: | mixed-strategy consideration: \nIf non-zero-sum → surplus: | mechanism: | structure: \nStrategic recommendation: \n```\n\n*→ Method in Action: [Von Neumann and the Foundation of Zero-Sum Analysis — RAND, 1944–1950](examples/von-neumann-rand-1944-1950.md)*\n\n## Game-Type Packs\n\n- **Financial Derivatives:** Zero-sum by contract — every dollar the long gains, the short loses. Minimax applies; cooperation with counterparties is structurally impossible.\n- **Market Share Competition:** Constant-sum short-term; non-zero-sum long-term (category growth, platform effects). Treating long-term markets as zero-sum causes destructive price wars.\n- **Licensing/Spectrum Auctions:** Zero-sum by design — fixed license count. Firms that bid cooperatively lose to rivals who bid to win.\n- **Trade and International Economics:** Non-zero-sum — comparative advantage produces mutual gains. \"Trade deficits = losses\" is an analytical error.\n\n## Applying It Well\n\n- Always state the contested resource precisely before diagnosing — \"competition\" is not a resource.\n- Confirm the time horizon: the same situation can be zero-sum this quarter and non-zero-sum over three years.\n- Non-zero-sum surplus must be *captured*, not just identified — without a credible mechanism it stays theoretical.\n- Zero-sum bias is strongest when resources are countable and socially salient (share rankings, polls). Build in a deliberate check before decisions driven by competitive intel.\n\n*→ Primary sources: [references/sources.md](references/sources.md)*\n\n## Common Rationalizations\n\n**[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.**\n\n| Fake move | Reality |\n|---|---|\n| [D] \"Our market share went down, so we lost\" | Share and value captured differ. If total market grew 50% and share fell 30%→25%, absolute revenue grew. |\n| [D] \"Trade deficits mean we're losing\" | Deficits in goods are offset by export of financial claims. Comparative advantage shows both parties gain. |\n| [D] \"They won the contract, so we lost it\" | One award is zero-sum among bidders. Total industry contracting volume is usually not fixed. |\n| [D] \"We should cooperate — there's value to be created\" | Only correct if non-zero-sum. In genuine zero-sum settings, \"cooperation\" is illegal or a strategic error. |\n| [D] \"It's just market share — zero-sum by definition\" | Market share is a ratio. The denominator is not fixed unless you freeze the time horizon. |\n| [D] \"They made money, so we left money on the table\" | In non-zero-sum negotiation both parties can gain. Counterparty's gain implies your loss only if truly zero-sum. |\n| [D] \"Race to the bottom on price — classic zero-sum\" | Zero-sum on margin within a fixed pool, but non-zero-sum if lower prices expand total demand. |\n| [D] \"My industry experience says it's zero-sum\" | Intuitions fail at inflection points. Run diagnosis from first principles on the current structure. |\n| *→ Add [O] entries here after each real use — paste the actual failure pattern* | *What went wrong and why* |\n\n## Red Flags\n\n- Contested resource never explicitly named or tested for fixity\n- \"Zero-sum\" concluded because competition *feels* intense, not from resource structure\n- Non-zero-sum used to justify cooperation without identifying a concrete surplus-capture mechanism\n- Time horizon not specified — \"zero-sum\" treated as time-invariant\n- Zero-sum bias not audited (countability, relative position, comparative advantage)\n- Minimax applied to a non-zero-sum situation; or cooperation proposed in a genuinely zero-sum situation\n\n## Verification\n\n- [ ] Contested resource named precisely with the specific unit being divided\n- [ ] Fixity test run on all three dimensions: technology, cooperation, time horizon\n- [ ] Zero-sum bias audited: countability, relative-position anchoring, comparative-advantage blindness\n- [ ] Diagnosis states game type with reasoning; time horizon specified for both short and long term\n- [ ] If zero-sum: minimax strategy identified including mixed-strategy consideration\n- [ ] If non-zero-sum: surplus estimated, mechanism named, structural capture mechanism proposed\n- [ ] Stop-rule applied: non-zero-sum confirmed by identifiable mechanism, not assumed from desire to cooperate\n\n---\n\n*Part of **deciqAI Knowledge Skills** — 163 open-source thinking skills that make rigor executable for AI agents. The same skills power every deciqAI agent, which runs them autonomously to operate your company. **See it run → https://www.deciqai.com/skills/zero-sum-game?utm_source=clawhub&utm_medium=marketplace&utm_campaign=knowledge-skills&utm_content=zero-sum-game** · ⭐ Star the repo → https://github.com/deciqAI/knowledge-skills · Contributions welcome.*\n\nFile v1.0.2:_meta.json\n\n{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"zero-sum-game\",\n \"version\": \"1.0.2\",\n \"publishedAt\": 1783472966023\n}\n\nFile v1.0.2:references/sources.md\n\n# Sources — zero-sum-game\n\n> *Primary sources for the [zero-sum-game](../SKILL.md) skill.*\n\n- Von Neumann, J. & Morgenstern, O. (1944). *Theory of Games and Economic Behavior.* Princeton University Press. The founding text of game theory; contains the Minimax Theorem and the formal definition of zero-sum games. Reprint available via Princeton University Press. https://press.princeton.edu/books/paperback/9780691130613/theory-of-games-and-economic-behavior\n- Schelling, T.C. (1960). *The Strategy of Conflict.* Harvard University Press. The canonical analysis of zero-sum vs. non-zero-sum conflict in negotiation and deterrence, including the Cold War application. https://www.hup.harvard.edu/books/9780674840317\n- Nash, J. F. (1950). \"Equilibrium Points in n-Person Games.\" *Proceedings of the National Academy of Sciences*, 36(1), pp. 48–49. The equilibrium concept that generalizes beyond zero-sum settings; for zero-sum games, Nash equilibrium coincides with minimax. https://doi.org/10.1073/pnas.36.1.48\n- Meegan, D.V. (2010). \"Zero-Sum Bias: Perceived Competition Despite Unlimited Resources.\" *Frontiers in Psychology*, 1, 191. Primary empirical documentation of zero-sum bias as a cognitive phenomenon — the systematic tendency to perceive zero-sum structures when they are not present. https://doi.org/10.3389/fpsyg.2010.00191\n- Dixit, A. & Nalebuff, B. (1991). *Thinking Strategically.* W.W. Norton. The standard practical treatment of zero-sum vs. non-zero-sum games for practitioners; Chapter 4 covers the distinction in business contexts. ISBN 978-0393310351.\n\n**What is not cited and why:** Popular business writing frequently attributes the phrase \"zero-sum game\" to competitive strategy without checking whether the specific situation meets the mathematical definition. Claims that \"competition is always zero-sum\" or \"negotiation is always zero-sum\" are asserted but unverified. This skill uses the mathematical definition from Von Neumann and Morgenstern as the anchor, not intuitive usage.\n\nFile v1.0.2:examples/von-neumann-rand-1944-1950.md\n\n# Method in Action: Von Neumann and the Foundation of Zero-Sum Analysis — RAND, 1944–1950\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nThe zero-sum framework did not originate as a business tool. It was developed to analyze nuclear deterrence.\n\nIn 1944, John von Neumann and Oskar Morgenstern published *Theory of Games and Economic Behavior*, establishing the mathematical foundation of game theory. Their central result for zero-sum games — the Minimax Theorem — had been proved by von Neumann in 1928: in any finite two-person zero-sum game, there exists a mixed-strategy pair such that neither player can improve their expected payoff by unilaterally deviating. The equilibrium payoff to each player is simultaneously the maximum of their minimum guarantee and the minimum of their maximum loss.\n\nBy 1950, RAND Corporation — the primary Cold War strategy think tank — was applying this framework to nuclear deterrence. The core question: is nuclear confrontation between the United States and USSR a zero-sum game? If yes, the minimax solution determines rational deterrence posture. If no — if both parties are worse off under nuclear exchange than under mutual restraint — the situation is a non-zero-sum game requiring a different analysis.\n\nRunning the Diagnosis on Cold War nuclear strategy:\n\n**Step 1 (contested resource):** Global political influence, territorial control, and the absence of nuclear exchange.\n\n**Step 2 (fixity test):** Political influence was partially zero-sum (Soviet gains in Europe meant Western losses). But the *survival of both nations* was non-zero-sum — nuclear exchange destroyed value for both sides simultaneously. Total welfare was not fixed: mutual restraint produced more total survival than mutual escalation.\n\n**Step 3 (bias audit):** Early Cold War strategists committed a countability error — they focused on the zero-sum dimension (territory, influence) and neglected the non-zero-sum dimension (mutual destruction). Schelling's *Strategy of Conflict* (1960) corrected this, showing that the deterrence game was fundamentally non-zero-sum because mutual destruction was the worst outcome for *both* players.\n\n**Step 4/5 (strategy):** Because the game was non-zero-sum, the correct strategy was not minimax but the design of *credible commitment devices* — each side needed to credibly commit to *not* launching a first strike in exchange for reciprocal restraint. Mutual Assured Destruction (MAD) was not a minimax strategy; it was a cooperative equilibrium sustained by credible commitment mechanisms (second-strike capability, hotlines, arms-control treaties).\n\n**Stop-rule applied:** The zero-sum diagnosis was limited to the political dimension. When strategists extended zero-sum reasoning to the nuclear dimension, they produced strategies (first-strike advantages, counterforce targeting) that the non-zero-sum structure showed were collectively irrational. The diagnosis prevented the most dangerous errors.\n\nPrimary sources: Von Neumann, J. & Morgenstern, O. (1944), *Theory of Games and Economic Behavior*, Princeton University Press; Schelling, T.C. (1960), *The Strategy of Conflict*, Harvard University Press.\n\nFile v1.0.2:skill-card.md\n\n## Description:
\nHelps agents determine whether a negotiation, market, policy, or competitive situation is truly zero-sum before choosing minimax, cooperation, or surplus-expansion strategy.
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[deciqai](https://clawhub.ai/user/deciqai)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nEmployees, external users, and strategy practitioners use this skill to diagnose whether a competitive situation has a fixed pie, audit zero-sum bias, and choose an appropriate strategic frame.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: Users may over-rely on the analysis in legal, financial, policy, or other high-stakes contexts.
\nMitigation: Treat the output as analytical guidance and seek appropriate expert review before acting on high-stakes recommendations.
\nRisk: The skill may misclassify a situation if the contested resource, time horizon, or surplus-capture mechanism is underspecified.
\nMitigation: Require a precise contested resource, an explicit time horizon, and a concrete mechanism before accepting a zero-sum or non-zero-sum diagnosis.
\n\n\n## Reference(s):
\n- [ClawHub Skill Page](https://clawhub.ai/deciqai/skills/zero-sum-game)
\n- [Sources](references/sources.md)
\n- [Von Neumann and the Foundation of Zero-Sum Analysis](examples/von-neumann-rand-1944-1950.md)
\n- [Theory of Games and Economic Behavior](https://press.princeton.edu/books/paperback/9780691130613/theory-of-games-and-economic-behavior)
\n- [The Strategy of Conflict](https://www.hup.harvard.edu/books/9780674840317)
\n- [Equilibrium Points in N-Person Games](https://doi.org/10.1073/pnas.36.1.48)
\n- [Zero-Sum Bias](https://doi.org/10.3389/fpsyg.2010.00191)
\n\n\n## Skill Output:
\n**Output Type(s):** [guidance, markdown, text]
\n**Output Format:** [Markdown diagnostic template with concise recommendations]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [No tools, shell commands, credentials, or external data access requested.]
\n\n## Skill Version(s):
\n1.0.2 (source: server release metadata)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
\n\nArchive v1.0.1: 5 files, 8975 bytes\n\nFiles: examples/von-neumann-rand-1944-1950.md (3207b), references/sources.md (2017b), skill-card.md (2695b), SKILL.md (9735b), _meta.json (132b)\n\nFile v1.0.1:SKILL.md\n\n---\nname: zero-sum-game\ndescription: \"Activate when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', uses phrases like 'winner-take-all', 'race to the bottom', or 'your gain is my loss', or needs to check whether a negotiation/market/policy situation is truly zero-sum before designing strategy.\n Do NOT activate when: the situation is already confirmed zero-sum (chess, derivatives, fixed-license auctions) and diagnosis is complete — go straight to minimax; or the question is already framed at the equilibrium level — use nash-equilibrium directly.\"\n---\n\n# Zero-Sum Game\n\n## Overview\n\nZero-sum means total value is fixed — one player's gain is another's exact loss. Most real-world competition is NOT zero-sum: the pie can grow, shrink, or be split in many ways. Misdiagnosis sends strategy in the wrong direction from step one. The most consequential error is **zero-sum bias**: the tendency to perceive non-zero-sum situations as zero-sum.\n\nNeighbor skills: use [`prisoners-dilemma`](../prisoners-dilemma/SKILL.md) when confirmed non-zero-sum but cooperation keeps failing. Use [`strategic-commitment`](../strategic-commitment/SKILL.md) when genuinely zero-sum and you need credible deterrence. Use [`nash-equilibrium`](../nash-equilibrium/SKILL.md) for the equilibrium solution in confirmed zero-sum settings.\n\n## When to Use\n\nApply this skill when: entering a competitive situation before determining whether total value is fixed; someone proposes a negotiation assuming \"what I gain, you lose\"; a market entry hinges on whether total market size is fixed; a policy analysis needs to assess whether an intervention redistributes or creates welfare; someone uses zero-sum language (\"winner-take-all\", \"race to the bottom\", \"fixed pie\").\n\n**When NOT to use:** already confirmed zero-sum — go straight to minimax; clear cooperative surplus with no competitive distribution problem; stakes trivial and reversible; question already at equilibrium level — use [`nash-equilibrium`](../nash-equilibrium/SKILL.md) directly.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** user has a concrete case → run The Process directly.\n- **Coach mode:** user is unfamiliar or has no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. **One-line what-it-is.** Zero-sum: total value fixed — if I get more, you get less by exactly the same amount. Most real-world competition is NOT zero-sum. The diagnosis changes everything about strategy.\n2. **Check fit.** Is the resource at stake genuinely fixed? If the total can change through cooperation, innovation, or trade, it is likely non-zero-sum.\n3. **Elicit the real case.** Get the specific situation — which market, which negotiation, which policy.\n> **[WAIT — do not advance until user responds]**\n4. **One step at a time.** Walk through the Diagnosis one question per turn. Start with: \"What exactly is being contested — and is the total amount of it fixed?\"\n> **[WAIT — do not advance until user responds]**\n5. **Close by naming the payoff.** State whether zero-sum or not, and what that means for strategy — cooperate/expand vs. minimax/capture.\n> **[WAIT — do not advance until user responds]**\n\n## The Process\n\nRun the **Zero-Sum Diagnosis**. Five gates; confirm or rule out at each one.\n\n1. **Define the contested resource.** State precisely what is being competed over (market share, license, price spread, votes, contract). If you cannot name a concrete unit being divided, the zero-sum frame likely does not apply.\n2. **Test fixity.** Can *innovation/technology* expand the total? Can *cooperation* create additional value? Can *time* change the total? If any answer is \"yes,\" the situation is non-zero-sum in that dimension.\n3. **Check for zero-sum bias.** Are you perceiving zero-sum because the resource is countable? Anchored on relative position over absolute gains? Ignoring comparative advantage? If expansion is feasible, you are in the wrong game.\n4. **If confirmed zero-sum: apply minimax.** Enumerate strategies and worst-case payoffs; choose the strategy maximizing your minimum; consider mixed strategies to prevent exploitation.\n5. **If confirmed non-zero-sum: design for cooperative surplus.** Quantify value neither party gets under pure competition. Specify the mechanism (contract, JV, standard, platform) to capture it. **Stop-rule:** if you cannot identify a concrete pie-growth mechanism, revert to zero-sum analysis.\n6. **State the time horizon.** Many situations are zero-sum short-term and non-zero-sum long-term. State both frames explicitly.\n\n### Output template\n\n```\nZero-Sum Diagnosis: \nContested resource: \nFixity test: innovation | cooperation | time \nBias audit: countability | relative-position | comparative-advantage ignored \nDiagnosis: — confidence \nIf zero-sum → minimax choice: | mixed-strategy consideration: \nIf non-zero-sum → surplus: | mechanism: | structure: \nStrategic recommendation: \n```\n\n*→ Method in Action: [Von Neumann and the Foundation of Zero-Sum Analysis — RAND, 1944–1950](examples/von-neumann-rand-1944-1950.md)*\n\n## Game-Type Packs\n\n- **Financial Derivatives:** Zero-sum by contract — every dollar the long gains, the short loses. Minimax applies; cooperation with counterparties is structurally impossible.\n- **Market Share Competition:** Constant-sum short-term; non-zero-sum long-term (category growth, platform effects). Treating long-term markets as zero-sum causes destructive price wars.\n- **Licensing/Spectrum Auctions:** Zero-sum by design — fixed license count. Firms that bid cooperatively lose to rivals who bid to win.\n- **Trade and International Economics:** Non-zero-sum — comparative advantage produces mutual gains. \"Trade deficits = losses\" is an analytical error.\n\n## Applying It Well\n\n- Always state the contested resource precisely before diagnosing — \"competition\" is not a resource.\n- Confirm the time horizon: the same situation can be zero-sum this quarter and non-zero-sum over three years.\n- Non-zero-sum surplus must be *captured*, not just identified — without a credible mechanism it stays theoretical.\n- Zero-sum bias is strongest when resources are countable and socially salient (share rankings, polls). Build in a deliberate check before decisions driven by competitive intel.\n\n*→ Primary sources: [references/sources.md](references/sources.md)*\n\n## Common Rationalizations\n\n**[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.**\n\n| Fake move | Reality |\n|---|---|\n| [D] \"Our market share went down, so we lost\" | Share and value captured differ. If total market grew 50% and share fell 30%→25%, absolute revenue grew. |\n| [D] \"Trade deficits mean we're losing\" | Deficits in goods are offset by export of financial claims. Comparative advantage shows both parties gain. |\n| [D] \"They won the contract, so we lost it\" | One award is zero-sum among bidders. Total industry contracting volume is usually not fixed. |\n| [D] \"We should cooperate — there's value to be created\" | Only correct if non-zero-sum. In genuine zero-sum settings, \"cooperation\" is illegal or a strategic error. |\n| [D] \"It's just market share — zero-sum by definition\" | Market share is a ratio. The denominator is not fixed unless you freeze the time horizon. |\n| [D] \"They made money, so we left money on the table\" | In non-zero-sum negotiation both parties can gain. Counterparty's gain implies your loss only if truly zero-sum. |\n| [D] \"Race to the bottom on price — classic zero-sum\" | Zero-sum on margin within a fixed pool, but non-zero-sum if lower prices expand total demand. |\n| [D] \"My industry experience says it's zero-sum\" | Intuitions fail at inflection points. Run diagnosis from first principles on the current structure. |\n| *→ Add [O] entries here after each real use — paste the actual failure pattern* | *What went wrong and why* |\n\n## Red Flags\n\n- Contested resource never explicitly named or tested for fixity\n- \"Zero-sum\" concluded because competition *feels* intense, not from resource structure\n- Non-zero-sum used to justify cooperation without identifying a concrete surplus-capture mechanism\n- Time horizon not specified — \"zero-sum\" treated as time-invariant\n- Zero-sum bias not audited (countability, relative position, comparative advantage)\n- Minimax applied to a non-zero-sum situation; or cooperation proposed in a genuinely zero-sum situation\n\n## Verification\n\n- [ ] Contested resource named precisely with the specific unit being divided\n- [ ] Fixity test run on all three dimensions: technology, cooperation, time horizon\n- [ ] Zero-sum bias audited: countability, relative-position anchoring, comparative-advantage blindness\n- [ ] Diagnosis states game type with reasoning; time horizon specified for both short and long term\n- [ ] If zero-sum: minimax strategy identified including mixed-strategy consideration\n- [ ] If non-zero-sum: surplus estimated, mechanism named, structural capture mechanism proposed\n- [ ] Stop-rule applied: non-zero-sum confirmed by identifiable mechanism, not assumed from desire to cooperate\n\n---\n\n*Part of **deciqAI Knowledge Skills** — open-source thinking skills that make rigor executable for AI agents. Built by deciqAI · https://deciqai.com · Contributions welcome — see the template at the repo root.*\n\nFile v1.0.1:_meta.json\n\n{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"zero-sum-game\",\n \"version\": \"1.0.1\",\n \"publishedAt\": 1783463713408\n}\n\nFile v1.0.1:references/sources.md\n\n# Sources — zero-sum-game\n\n> *Primary sources for the [zero-sum-game](../SKILL.md) skill.*\n\n- Von Neumann, J. & Morgenstern, O. (1944). *Theory of Games and Economic Behavior.* Princeton University Press. The founding text of game theory; contains the Minimax Theorem and the formal definition of zero-sum games. Reprint available via Princeton University Press. https://press.princeton.edu/books/paperback/9780691130613/theory-of-games-and-economic-behavior\n- Schelling, T.C. (1960). *The Strategy of Conflict.* Harvard University Press. The canonical analysis of zero-sum vs. non-zero-sum conflict in negotiation and deterrence, including the Cold War application. https://www.hup.harvard.edu/books/9780674840317\n- Nash, J. F. (1950). \"Equilibrium Points in n-Person Games.\" *Proceedings of the National Academy of Sciences*, 36(1), pp. 48–49. The equilibrium concept that generalizes beyond zero-sum settings; for zero-sum games, Nash equilibrium coincides with minimax. https://doi.org/10.1073/pnas.36.1.48\n- Meegan, D.V. (2010). \"Zero-Sum Bias: Perceived Competition Despite Unlimited Resources.\" *Frontiers in Psychology*, 1, 191. Primary empirical documentation of zero-sum bias as a cognitive phenomenon — the systematic tendency to perceive zero-sum structures when they are not present. https://doi.org/10.3389/fpsyg.2010.00191\n- Dixit, A. & Nalebuff, B. (1991). *Thinking Strategically.* W.W. Norton. The standard practical treatment of zero-sum vs. non-zero-sum games for practitioners; Chapter 4 covers the distinction in business contexts. ISBN 978-0393310351.\n\n**What is not cited and why:** Popular business writing frequently attributes the phrase \"zero-sum game\" to competitive strategy without checking whether the specific situation meets the mathematical definition. Claims that \"competition is always zero-sum\" or \"negotiation is always zero-sum\" are asserted but unverified. This skill uses the mathematical definition from Von Neumann and Morgenstern as the anchor, not intuitive usage.\n\nFile v1.0.1:examples/von-neumann-rand-1944-1950.md\n\n# Method in Action: Von Neumann and the Foundation of Zero-Sum Analysis — RAND, 1944–1950\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nThe zero-sum framework did not originate as a business tool. It was developed to analyze nuclear deterrence.\n\nIn 1944, John von Neumann and Oskar Morgenstern published *Theory of Games and Economic Behavior*, establishing the mathematical foundation of game theory. Their central result for zero-sum games — the Minimax Theorem — had been proved by von Neumann in 1928: in any finite two-person zero-sum game, there exists a mixed-strategy pair such that neither player can improve their expected payoff by unilaterally deviating. The equilibrium payoff to each player is simultaneously the maximum of their minimum guarantee and the minimum of their maximum loss.\n\nBy 1950, RAND Corporation — the primary Cold War strategy think tank — was applying this framework to nuclear deterrence. The core question: is nuclear confrontation between the United States and USSR a zero-sum game? If yes, the minimax solution determines rational deterrence posture. If no — if both parties are worse off under nuclear exchange than under mutual restraint — the situation is a non-zero-sum game requiring a different analysis.\n\nRunning the Diagnosis on Cold War nuclear strategy:\n\n**Step 1 (contested resource):** Global political influence, territorial control, and the absence of nuclear exchange.\n\n**Step 2 (fixity test):** Political influence was partially zero-sum (Soviet gains in Europe meant Western losses). But the *survival of both nations* was non-zero-sum — nuclear exchange destroyed value for both sides simultaneously. Total welfare was not fixed: mutual restraint produced more total survival than mutual escalation.\n\n**Step 3 (bias audit):** Early Cold War strategists committed a countability error — they focused on the zero-sum dimension (territory, influence) and neglected the non-zero-sum dimension (mutual destruction). Schelling's *Strategy of Conflict* (1960) corrected this, showing that the deterrence game was fundamentally non-zero-sum because mutual destruction was the worst outcome for *both* players.\n\n**Step 4/5 (strategy):** Because the game was non-zero-sum,\n\nArchive v1.0.0: 5 files, 8923 bytes\n\nFiles: examples/von-neumann-rand-1944-1950.md (3207b), references/sources.md (2017b), skill-card.md (2476b), SKILL.md (9735b), _meta.json (132b)","readmeExcerpt":"Skill: Zero-Sum Game Owner: deciqai Summary: Activate when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', u... Tags: latest:1.0.6 Version history: v1.0.6 | 2026-07-16T18:22:27.731Z | user Description tail link + agents machine-readable metadata line (deciqai.com/s/zero-sum-game.json) v1.0.5 | 2026-07-09T11:22:58.435Z | user","codeSnippets":[],"executableExamples":[{"language":"text","snippet":"Zero-Sum Diagnosis: \nContested resource: \nFixity test: innovation | cooperation | time \nBias audit: countability | relative-position | comparative-advantage ignored \nDiagnosis: — confidence \nIf zero-sum → minimax choice: | mixed-strategy consideration: \nIf non-zero-sum → surplus: | mechanism: | structure: \nStrategic recommendation: "},{"language":"text","snippet":"Zero-Sum Diagnosis: \nContested resource: \nFixity test: innovation | cooperation | time \nBias audit: countability | relative-position | comparative-advantage ignored \nDiagnosis: — confidence \nIf zero-sum → minimax choice: | mixed-strategy consideration: \nIf non-zero-sum → surplus: | mechanism: | structure: \nStrategic recommendation: "},{"language":"text","snippet":"Zero-Sum Diagnosis: \nContested resource: \nFixity test: innovation | cooperation | time \nBias audit: countability | relative-position | comparative-advantage ignored \nDiagnosis: — confidence \nIf zero-sum → minimax choice: | mixed-strategy consideration: \nIf non-zero-sum → surplus: | mechanism: | structure: \nStrategic recommendation: "},{"language":"text","snippet":"Zero-Sum Diagnosis: \nContested resource: \nFixity test: innovation | cooperation | time \nBias audit: countability | relative-position | comparative-advantage ignored \nDiagnosis: — confidence \nIf zero-sum → minimax choice: | mixed-strategy consideration: \nIf non-zero-sum → surplus: | mechanism: | structure: \nStrategic recommendation: "},{"language":"text","snippet":"Zero-Sum Diagnosis: \nContested resource: \nFixity test: innovation | cooperation | time \nBias audit: countability | relative-position | comparative-advantage ignored \nDiagnosis: — confidence \nIf zero-sum → minimax choice: | mixed-strategy consideration: \nIf non-zero-sum → surplus: | mechanism: | structure: \nStrategic recommendation: "},{"language":"text","snippet":"Zero-Sum Diagnosis: \nContested resource: \nFixity test: innovation | cooperation | time \nBias audit: countability | relative-position | comparative-advantage ignored \nDiagnosis: — confidence \nIf zero-sum → minimax choice: | mixed-strategy consideration: \nIf non-zero-sum → surplus: | mechanism: | structure: \nStrategic recommendation: "}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: zero-sum-game\ndescription: \"Activate when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', uses phrases like 'winner-take-all', 'race to the bottom', or 'your gain is my loss', or needs to check whether a negotiation/market/policy situation is truly zero-sum before designing strategy.\n Do NOT activate when: the situation is already confirmed zero-sum (chess, derivatives, fixed-license auctions) and diagnosis is complete — go straight to minimax; or the question is already framed at the equilibrium level — use nash-equilibrium directly. More: deciqai.com/c/zero-sum-game\"\n---\n\n# Zero-Sum Game\n\n## Overview\n\nZero-sum means total value is fixed — one player's gain is another's exact loss. Most real-world competition is NOT zero-sum: the pie can grow, shrink, or be split in many ways. Misdiagnosis sends strategy in the wrong direction from step one. The most consequential error is **zero-sum bias**: the tendency to perceive non-zero-sum situations as zero-sum.\n\nNeighbor skills: use `prisoners-dilemma` when confirmed non-zero-sum but cooperation keeps failing. Use `strategic-commitment` when genuinely zero-sum and you need credible deterrence. Use `nash-equilibrium` for the equilibrium solution in confirmed zero-sum settings.\n\n## When to Use\n\nApply this skill when: entering a competitive situation before determining whether total value is fixed; someone proposes a negotiation assuming \"what I gain, you lose\"; a market entry hinges on whether total market size is fixed; a policy analysis needs to assess whether an intervention redistributes or creates welfare; someone uses zero-sum language (\"winner-take-all\", \"race to the bottom\", \"fixed pie\"); or someone frames the AI race, AI capex/compute buildout, AI-talent competition, or AI-native market entry as a single winner-take-all contest and you need to separate the genuinely fixed inputs (near-term compute/talent) from the growing pie (AI-driven productivity and adoption).\n\n**When NOT to use:** already confirmed zero-sum — go straight to minimax; clear cooperative surplus with no competitive distribution problem; stakes trivial and reversible; question already at equilibrium level — use `nash-equilibrium` directly.\n\n## Coaching Novices (Adaptive Front Door)\n\n- **Engine mode:** user has a concrete case → run The Process directly.\n- **Coach mode:** user is unfamiliar or has no concrete case → guide step by step.\n\nIn Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.\n\n1. **One-line what-it-is.** Zero-sum: total value fixed — if I get more, you get less by exactly the same amount. Most real-world competition is NOT zero-sum. The diagnosis changes everything about strategy.\n2. **Check fit.** Is the resource at stake genuinely fixed? If the total can change through cooperation, innovation, or trade, it is likely non-zero-sum.\n3. **Elicit the real "},{"path":"_meta.json","content":"{\n \"ownerId\": \"kn754b8sk22s8c6gjxt02bftbn88q7ye\",\n \"slug\": \"zero-sum-game\",\n \"version\": \"1.0.6\",\n \"publishedAt\": 1784226147731\n}"},{"path":"references/sources.md","content":"# Sources — zero-sum-game\n\n> *Primary sources for the [zero-sum-game](../SKILL.md) skill.*\n\n- Von Neumann, J. & Morgenstern, O. (1944). *Theory of Games and Economic Behavior.* Princeton University Press. The founding text of game theory; contains the Minimax Theorem and the formal definition of zero-sum games. Reprint available via Princeton University Press. https://press.princeton.edu/books/paperback/9780691130613/theory-of-games-and-economic-behavior\n- Schelling, T.C. (1960). *The Strategy of Conflict.* Harvard University Press. The canonical analysis of zero-sum vs. non-zero-sum conflict in negotiation and deterrence, including the Cold War application. https://www.hup.harvard.edu/books/9780674840317\n- Nash, J. F. (1950). \"Equilibrium Points in n-Person Games.\" *Proceedings of the National Academy of Sciences*, 36(1), pp. 48–49. The equilibrium concept that generalizes beyond zero-sum settings; for zero-sum games, Nash equilibrium coincides with minimax. https://doi.org/10.1073/pnas.36.1.48\n- Meegan, D.V. (2010). \"Zero-Sum Bias: Perceived Competition Despite Unlimited Resources.\" *Frontiers in Psychology*, 1, 191. Primary empirical documentation of zero-sum bias as a cognitive phenomenon — the systematic tendency to perceive zero-sum structures when they are not present. https://doi.org/10.3389/fpsyg.2010.00191\n- Dixit, A. & Nalebuff, B. (1991). *Thinking Strategically.* W.W. Norton. The standard practical treatment of zero-sum vs. non-zero-sum games for practitioners; Chapter 4 covers the distinction in business contexts. ISBN 978-0393310351.\n- Irwin, D.A. (2011). *Peddling Protectionism: Smoot-Hawley and the Great Depression.* Princeton University Press. The definitive historical account of the 1930 tariff — the political economy of its passage, the foreign retaliation it provoked, and its role in the collapse and fragmentation of world trade; the canonical documented case of zero-sum misdiagnosis in trade policy. ISBN 978-0691150321.\n\n- International Energy Agency (2025). *Energy and AI* (World Energy Outlook Special Report), published April 2025. IEA, Paris. Documents the 2024–2025 scale-up of AI compute and data-center demand, and the physical constraints (power, hardware supply, lead times) that bound near-term capacity — useful for grounding the \"near-term compute is a fixed input\" side of the AI zero-sum diagnosis. https://www.iea.org/reports/energy-and-ai\n- Stanford HAI (2025). *Artificial Intelligence Index Report 2025,* published April 2025. Stanford Institute for Human-Centered AI. Tracks model performance, investment, adoption, and compute trends through 2024 — the widely cited public baseline for the state of AI competition, capital expenditure, and the concentration of frontier capability and talent. https://hai.stanford.edu/ai-index/2025-ai-index-report\n\n**What is not cited and why:** Popular business writing frequently attributes the phrase \"zero-sum game\" to competitive strategy without checking whether the specific situati"},{"path":"examples/ai-competition-fixed-vs-growing-pie-2024-2026.md","content":"# Method in Action: Where the AI Race Is Zero-Sum and Where It Isn't (2024–2026)\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nBy 2024–2026 the dominant framing of the AI boom was a single \"race\" — one leaderboard, one winner, everyone else loses. That framing quietly bundles together resources with very different structures. Some inputs to AI are genuinely fixed in the near term and therefore zero-sum; the output — AI-driven productivity — is not. Treating the whole thing as one zero-sum contest is exactly the diagnosis error this skill is built to catch: it pushes firms toward pure capture (outbid rivals, hoard talent, block competitors) when part of the game rewards expansion (build the market, enlarge supply, complement rather than substitute).\n\nThe point of the diagnosis is that \"the AI race\" is not one game — it is a **mixed** game, and you have to name the resource before you know which move applies.\n\nRunning the Diagnosis:\n\n**Step 1 (define the contested resource).** Split \"AI competition\" into its distinct contested resources rather than treating it as one blob:\n- *Near-term advanced-chip and high-bandwidth-memory (HBM) supply* — the units of leading-edge accelerators and the HBM stacks they require, buildable only through a small number of suppliers with long lead times.\n- *Top-tier AI research talent* — the small pool of people who have actually trained frontier systems.\n- *AI-driven productivity / the value AI creates for end users* — the output the whole boom is ostensibly about.\n\nEach is a nameable, distinct unit. That is the precondition for a real diagnosis; \"who wins AI\" is not a resource.\n\n**Step 2 (test fixity) — run separately per resource:**\n- *Chips/HBM, near term:* **fixed.** Leading-edge fabrication and advanced-memory capacity cannot be expanded on a quarterly horizon — it is gated by a handful of suppliers and multi-year fab and packaging build-outs. Within a given year, one buyer's allocation is largely another's shortfall. **Zero-sum (near term).**\n- *Top talent, near term:* **fixed.** The pool of people who have led frontier training runs is small and slow to grow. A senior hire at one lab is, for that cycle, a hire the rival did not get. **Zero-sum (near term).**\n- *AI productivity / end-user value:* **not fixed.** Cooperation and innovation expand it — better models, cheaper inference, and new applications enlarge total value created rather than merely reallocating it. One firm shipping a useful AI product does not consume the possibility of another firm shipping one. **Non-zero-sum.**\n- *Time dimension:* the fixity of chips and talent is a **near-term** property. Over a multi-year horizon, supply responds — new fab and advanced-packaging capacity comes online and the trained-talent pool grows — so even these resources become less zero-sum the longer the horizon.\n\n**Step 3 (check for zero-sum bias).** The popular \"one race, one winner\" frame shows all three bias markers on the *productivity* dimension:\n-"},{"path":"examples/smoot-hawley-tariff-1930.md","content":"# Method in Action: The Smoot-Hawley Tariff and the Fixed-Pie Fallacy in Trade (1930–1934)\n\n> *Example for the [zero-sum-game](../SKILL.md) skill.*\n\nThe Smoot-Hawley Tariff Act of 1930 is the most consequential documented case of zero-sum misdiagnosis in economic policy — a strategy built on the assumption that trade is a fixed pie, executed at national scale, with measurable results.\n\nThe implicit diagnosis behind the tariff: imports capture American production and jobs, so every unit of imports blocked is a unit of domestic output gained. On this logic, Congress raised duties on over 20,000 imported goods, and President Hoover signed the act in June 1930 — over a petition signed by more than a thousand economists urging a veto. The economists' objection was precisely a zero-sum objection: trade is mutual gain via comparative advantage, and blocking it destroys value on both sides rather than transferring it.\n\nRunning the Diagnosis on the 1930 decision:\n\n**Step 1 (contested resource):** Domestic production and employment in import-competing sectors. Nameable and countable — which is exactly the condition under which zero-sum bias is strongest.\n\n**Step 2 (fixity test):** Fails on all three dimensions. *Cooperation:* trade itself is the cooperative mechanism — specialization by comparative advantage makes total output larger than under autarky, so the \"pie\" of production is not fixed. *Innovation/technology:* export industries expand when trading partners prosper. *Time:* even if a tariff transfers demand to domestic producers this quarter, retaliation and shrinking foreign incomes cut export demand over the following years.\n\n**Step 3 (bias audit):** All three bias markers present. Countability — imports arrive in visible, countable units at ports, while the diffuse gains from trade do not. Relative-position anchoring — the political debate framed foreign producers' sales as America's losses. Comparative-advantage blindness — the analysis treated a dollar of imports as a dollar of forgone domestic production, ignoring that both sides gain from specialization.\n\n**Step 4/5 (what the wrong diagnosis produced):** Because policymakers treated a non-zero-sum game as zero-sum, they played capture instead of designing for surplus. Trading partners ran the same wrong playbook in reverse: Canada — the largest US trading partner — retaliated with duties targeting US exports, and other countries followed with tariffs, quotas, and preferential blocs. Both moves were individually \"rational\" under the fixed-pie frame and collectively destructive outside it. Between 1929 and 1933 world trade collapsed to a fraction of its former volume; the Depression drove much of the fall, but as Irwin documents, the tariff and the retaliation it provoked deepened the contraction and fragmented the world trading system into discriminatory blocs. The pie did not get redivided — it shrank for everyone.\n\n**The corrected diagnosis:** The reversal came only when the game was reframe"}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"Activate when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', u... Skill: Zero-Sum Game Owner: deciqai Summary: Activate when: someone asks 'are we fighting over a fixed pie?', 'should we cooperate or compete?', 'is the market growing or are we just stealing share?', u... 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